Artificial Intelligence Could Save the Healthcare Industry Billions!

A report by Harvard University researchers has found that large-scale adoption of AI could save the American healthcare system nearly $400 billion annually.

The improvements that AI implementation in hospitals and other medical facilities can accomplish for patient care are becoming fairly well known. A little less obvious is the impact that AI can have on skyrocketing health costs.

Joint researchers with McKinsey & Company and Harvard University have found that widespread adoption of artificial intelligence in healthcare could save the US up to $360 billion annually.

For various reasons, the healthcare industry has a relatively low adoption of AI-based tools despite the benefits discovered by researchers and early adopters. In the new paper, researchers estimate that the broader adoption of AI in the healthcare industry could lead to savings in the range of 5% to 10% in healthcare spending, or between approximately $200 billion and $360 billion per year. Their estimates are based on AI use cases utilizing current technologies that are achievable within the next five years, without compromising quality or access.

The researchers say that hospitals could see cost savings mainly through improved clinical operations, quality, and safety – such as optimizing operating rooms or identifying adverse events. Physician groups can experience similar benefits by leveraging AI for continuity of care, such as referral management.

Similar savings could be experienced by health insurers as AI solutions can streamline their operations and work to reduce waste and fraud. The researchers concluded that insurance providers could experience savings from AI solutions that improve claims management, such as automating prior authorization, along with those that can enhance healthcare and provider relationship management, including preventing readmissions and provider directory management.

Based on AI-driven use cases, the researchers claim that private payers could save approximately 7% to 9% of their total costs, or between $80 billion and $110 billion annually, all within the next five years. Physician groups could save 3% to 8% of their costs, translating into savings of between $20 billion and $60 billion.

How BigRio Helps Facilitate Advancement in Healthcare AI

At BigRio, we understand how AI is changing the very nature of healthcare delivery in America, which is why our premier mission is to partner with startups to develop healthcare initiatives with AI at the core of their solutions.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:

• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.

• Assistance in the development and testing of the MVP, Prototypes, and POCs.

• Professional services for implementation and support of Pilot projects

• Sales and Marketing support and potential client introductions.

• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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AI Joins the Search for Extraterrestrial Life!

The search for signs of intelligent extraterrestrial life has been joined by a specialized AI initiative known as “Breakthrough Listen.”

Artificial Intelligence, or AI, has been revolutionizing many areas of scientific research; most notably, as we have often written about in these pages, AI is dramatically changing medical research and drug discovery. Now AI is being leveraged for a discovery of a different sort. Breakthrough Listen is an AI-driven initiative searching for “technosignatures,” or signs of intelligent life in the universe.

In a paper published in the journal Nature Astronomy, the team analyzed 480 hours of data from the Green Bank Telescope (GBT) in West Virginia and reported eight previously undetected signals of interest that have certain characteristics expected of genuine technosignatures.

“The key issue with any technosignature search is looking through this huge haystack of signals to find the needle that might be a transmission from an alien world,” explained Dr. Steve Croft, an astrophysicist with the Breakthrough Listen team at the University of California, Berkeley. The vast majority of the signals detected by our telescopes originate from our own technology – GPS satellites, mobile phones, and the like. Peter’s algorithm gives us a more effective way to filter the haystack and find signals that have the characteristics we expect from technosignatures.”

Classical technosignature algorithms compare scans where the telescope is pointed at a target point in the sky with scans when the telescope moves to a nearby position in order to identify signals that may be coming from only that specific point. These techniques are highly effective – for example, they can successfully identify the Voyager 1 space probe at a distance of 20 billion kilometers. But these algorithms struggle in crowded regions of the radio spectrum, where the challenge is akin to listening for a whisper in a crowded room.

The Breakthrough Listen team is led by University of Toronto undergraduate student Peter Ma, who began working with the team while still in high school and a student of Dr. Croft’s.

The process developed by Ma inserts simulated signals into real data and trains an AI algorithm known as an “autoencoder” to learn their fundamental properties. The output from this process is fed into a second algorithm known as a “random forest classifier,” which learns to distinguish the candidate signals from the noisy background.

“In 2021, our classical algorithms uncovered a signal of interest, denoted BLC1, in data from the Parkes telescope,” said Dr. Andrew Siemion, Breakthrough Listen’s Principal Investigator. “Peter’s algorithm is even more effective in finding signals like this. Any technosignature candidate needs to be confirmed, however, and when we looked at these targets again with the GBT, the signals did not reappear. But by applying this new technique to even larger datasets, we can more effectively identify technosignature candidates, and hopefully eventually even a confirmed technosignature.”

“It’s exciting to see new approaches like this being developed by imaginative young people like Peter at the beginning of their scientific careers,” said Breakthrough Initiatives Executive Director Dr. S. Pete Worden. “We’ll continue to monitor the stars Peter observed, and we’ll continue to develop our use of artificial intelligence to help us try to answer humanity’s most profound question: are we alone?”

How BigRio Helps Bring Advanced AI Solutions to All Areas of Research

The announcement of AI being used in unique ways by young innovative minds like Peter Ma has done to enhance the search for extraterrestrial intelligence is what BigRio is all about. We pride ourselves on being a facilitator and incubator for such advances in leveraging AI to improve the world.

In fact, we like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting out in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the Sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the expertise to not only weed out the companies that are not ready for the market, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the AI investment community.

You can read much more about how AI is redefining scientific research in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into AI in general, with specific chapters on IoT and NLP technologies.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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A Major Hurdle to Large-Scale Implementation of Quantum Computing Has Been Overcome!

The promises of quantum computing, particularly when combined with AI, are many. However, the technology, while being used in some real-world applications, is still in its infancy, and there are many hurdles yet to be overcome before quantum computers can be implemented on a large scale. However, researchers with Sussex University report that they may have just overcome one of them.

The scientists say that they have managed to transfer data between chips at record speeds and – more importantly – record accuracy.

“What we have achieved here is the ability to realize extremely powerful quantum computers capable of solving some of the most important problems for industries and society,” said lead researcher Prof Winfried Hensinger.

The foundation of the power of quantum computing is drawn from quantum physics, hence its name. Without getting into a complex discussion beyond the scope of this article, quantum computing relies on one of the driving principles of quantum mechanics, namely that subatomic particles can literally exist in two places at the same time and can be in a state of “quantum attachment” mirroring each other’s actions almost simultaneously across unfathomable distances.

Leveraging these properties in the computational space means that quantum computers could potentially handle multiple processes at speeds not possible with even today’s most advance “supercomputers.”

One of the major obstacles to the technology’s development has been the ability to transfer information across chips, so it remains intact. Quantum computers, by design, are highly sensitive and therefore have a low fault tolerance. That means that the slightest interferences can disrupt their effective operation.

The research team at Sussex University demonstrated a way to transfer information between quantum chips with 99.999993% reliability, and the connection rate was 2424/s.

Both set world records, the researchers say, and show it’s possible for quantum chips to be fitted together to build more powerful quantum computers.

Director of the National Quantum Computing Centre, Prof Michael Cuthbert, commented on the findings.

“To build the type of quantum computer you need in the future, you start off by connecting chips that are the size of your thumbnail until you get something the size of a dinner plate. The Sussex group has shown you can have the stability and speed for that step.”

How is This Discovery Relevant to AI?

It is quantum computers that will create astronomical changes in the field of AI. Currently, it can take months to train an AI model to become effective. Quantum computing will speed up AI and machine learning by considerable orders of magnitude.

In fact, IBM has already revealed mathematical proof that quantum machine learning is exponentially faster than standard methods of ML, as long as “one can provide classical data to the algorithm in the form of quantum states.” Although it remains theoretical at this point, if it can be applied, then the future for AI and quantum computing looks very promising indeed.

Furthermore, and perhaps even more significant to the Sussex discoveries, is that the ultimate goal of AI is to recreate, as close as possible, the human mind. Prof Hensinger and his team’s “quantum chip-to-chip” nearly instantaneous transfer of information behaved very much like the neuron-to-neuron communications of the brain. This could have an astounding impact on AI and put us on the path to computers that can truly “think” like humans in every way.

How Big Rio Can Help

Quantum computing is still very much an emerging technology with large-scale and practical applications still a way off. However, the technology is steadily graduating from the lab and heading for the marketplace. In 2019, Google announced that it had achieved “quantum supremacy,” IBM has committed to doubling the power of its quantum computers every year, and numerous other companies and academic institutions are investing billions toward making quantum computing a commercial reality.

Quantum computing will take artificial intelligence and machine learning to the next level. The marriage between the two is an area to pay very close attention to for startups as well as for where Big Tech will be going over the next five to ten years, and where ever this road can take use BigRio will be there to help get startups and society as a whole to its ultimate destination.

You can read much more about how quantum computing will redefine AI and machine learning in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI is being used to improve healthcare and society as a whole.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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Researchers Combine AI and the Internet of Things to Track Progression of Movement Disorders

Researchers have combined wearable “Fitbit”-type technology with AI to better track and monitor movement disorders.

In two ground-breaking studies, published in Nature Medicine, a cross-disciplinary team of AI and clinical researchers have shown that by combining human movement data gathered from wearable tech with a powerful new medical AI technology, they are able to identify clear movement patterns, predict future disease progression and significantly increase the efficiency of clinical trials in two very different rare disorders, Duchenne muscular dystrophy (DMD) and Friedreich’s ataxia (FA).

DMD and FA are rare, degenerative genetic diseases that affect movement and eventually lead to paralysis. There are currently no cures for either disease, but researchers hope that these results will significantly speed up the search for new treatments.

Scientists hope that, as well as using the technology to monitor patients in clinical trials; it could also one day be used to monitor or diagnose a range of common diseases that affect movement behavior, such as dementia, stroke, and orthopedic conditions.

Senior and corresponding author of both papers, Professor Aldo Faisal, from Imperial College London’s Departments of Bioengineering and Computing, who is also Director of the UKRI Center for Doctoral Training in AI for Healthcare, and the Chair for Digital Health at the University of Bayreuth (Germany), and a UKRI Turing AI Fellowship holder, said, “Our approach gathers huge amounts of data from a person’s full-body movement—more than any neurologist will have the precision or time to observe in a patient.

“Our AI technology builds a digital twin of the patient and allows us to make unprecedented, precise predictions of how an individual patient’s disease will progress.

“We believe that the same AI technology working in two very different diseases shows how promising it is to be applied to many diseases and help us to develop treatments for many more diseases even faster, cheaper, and more precisely.”

AI, Healthcare, and the Internet of Things

These two studies are just another example of how AI is being combined with the Internet of Things (IoT) for advanced diagnostics, earlier detection of disease, and better patient outcomes.

The Internet of Things (IoT), sometimes also referred to as The Internet of Everything (IoE), is a term used to describe the network of physical objects that we know as the “smart things” which are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet.

In terms of healthcare, it can readily be seen how IoT allows for the interactivity between bedside monitors, smartwatches, fitness trackers, implanted medical devices, and any other “thing” that transmits or receives a signal containing pertinent medical data that can then be accessed or stored from or to anywhere.

In broad terms, IoT is changing the very nature of data acquisition and data analytics as they are applied to healthcare, transforming both into something far deeper and more powerful.

Traditionally, healthcare organizations currently base most of their clinical and financial analytics on conventional data sources like EHRs, insurance claims data, and lab results. But now, thanks to the Internet of Things, they are starting to integrate behavioral data from clients’ credit cards or fitness data from health trackers and smartphone data, including searches for health topics and likes on social media.

Add to that all of the “things” such as remote monitoring from internet-connected prescription bottles, Bluetooth-connected scales, or wearable devices such as in Professor Faisal’s studies, – and it is easy to see how IoT is bringing a vastness and richness of data to healthcare that was never before possible and can improve patient care across the board.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

Like the muscle movement studies, leveraging IoT solutions for medical applications is an area where AI is making one of the technology’s biggest impacts in healthcare.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI and IoT tech to improve healthcare delivery and drug discovery. In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:
• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
• Assistance in the development and testing of the MVP, Prototypes, and POCs.
• Professional services for implementation and support of Pilot projects
• Sales and Marketing support and potential client introductions.
• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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Microsoft Partners to Develop AI-Based Healthcare Services

An exciting partnership between computing and graphics giant Nvidia and AI startup Evozyne has announced that they have been able to produce novel versions of a human protein that has never been seen in nature — but with “enhanced function” and the same safety as native proteins. The researchers say that the AI breakthrough lays the groundwork for potential new therapies for rare disorders.

Tech giant Microsoft is partnering with Vietnam-based AI conglomerate VinBrain to develop artificial intelligence-based healthcare services.

Under the collaboration, the two companies will work together to work on three areas of healthcare AI — data sharing, cross-product validation, and research and development, according to a recent press release from VinBrain.

VinBrain will also use Microsoft’s Azure Cognitive Services for computer vision to validate new deep-learning models.

The aim of the partnership is to accelerate the development of AI products in the health technology space. According to VinBrain, the AI platform runs on a dataset of over 2 million images sourced from multiple regions – the United States, Asia, and Europe. These data will be shared via Microsoft Azure, which will also ensure privacy and security, manage ever-changing compliance regulations, and improve data governance.

As part of the collaboration, VinBrain will also use Azure Cognitive Services for Computer Vision to validate new deep-learning models, including Microsoft’s latest computer vision model called Florence.

Accroding to the two companies the goal of the collaboration is to leverage AI to be applied to improve medical services in remote areas where there are limited medical facilities. “On the social aspect, this will help speed up the process of resolving [the] increasing number of healthcare issues with a lack of infrastructure, uneven doctor-to-patient ratio, and increased demand for healthcare services,” they said in a joint statement.

For VinBrain CEO Steven Truong, this partnership will deepen the company’s focus on and boost its development of AI products in the health technology space. “Using the latest foundation of AI technology and evaluation, this collaboration with Microsoft will directly impact billions of people through early [disease] detection and workflow productivity,” he added.

Perhaps equally important, the partnership, the first between Microsoft and a major player in the AI space from Vietnam is seen to open up opportunities for Microsoft to expand its presence in Southeast Asia’s healthcare scene.

 

How BigRio Helps Facilitate Investment in AI Startups

Much like the collaboration between Microsoft and VinBrain, BigRio is partnering with startups to develop healthcare initiatives with AI at the core of their solutions.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:
• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
• Assistance in the development and testing of the MVP, Prototypes, and POCs.
• Professional services for implementation and support of Pilot projects
• Sales and Marketing support and potential client introductions.
• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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How Artificial Intelligence Is Improving Telemedicine

Telemedicine or telehealth services were already on the upswing before the arrival of the COVID-19 pandemic. Since the pandemic, as we were forced into quarantine, more patients and many more doctors and healthcare facilities became reliant on telehealth – pushing advancement in telehealth apps. Telemedicine apps needed to become broader, faster, more interactive, more intuitive, and more accurate — a need that was successfully fulfilled by AI.

AI is being increasingly used in telemedicine to allow doctors to make more data-driven, real-time decisions that may improve the patient experience and health outcomes.

According to a study from MIT, 75% of healthcare facilities that utilized AI reported improved capacity to manage illnesses, and 4/5 said that AI aided in reducing employee fatigue. AI in healthcare is a promising strategy for the future of telemedicine applications, given that COVID-19 continues to place a strain on both the volume of patient data analysis and the number of people who need medical attention.

In one example cited in the MIT study, an AI-integrated system was used to help a doctor in India manage his telehealth patient load. The system, which was designed by US-based company Welltok, was able to provide real-time analysis of the doctor’s interactions with patients and make recommendations on how he could improve his care. Telehealth solutions like these lower the burdens on health plans, providers, and employer benefit managers while providing an on-demand customized experience for patients.

According to Welltok, its AI “chatbot” has an accuracy rate of 98 percent and was found to save consumers time by over 60%.

Virtual nursing assistants are another way that AI is being used to deliver improved telehealth services. These assistants use natural language processing (NLP) to understand questions asked by patients and provide answers based on information from their electronic health records.

One example of a virtual nursing assistant is the app NurseWise, which was developed by the American Nurses Association. This app provides nursing advice and guidance to patients 24/hours a day, seven days a week.

Another progressive use of telehealth, also driven by the pandemic, was the increased use of RPM, which stands for remote patient monitoring. RPM is a way to gather and transmit patient health data to medical specialists outside of a doctor’s office or a clinical environment via linked technology. RPM leverages AI and Internet of Things technologies such as the Apple Watch, Google Fit, and other wearables to collect patient information and other vital signs like heart rates, sleep patterns, and physical activity levels.

Thanks to advances in AI, telehealth is becoming more widely available and affordable, making it easier for people to get the care they need without having to ever leave their homes!

How BigRio is Helping to Advance Telehealth

At BigRio, we like to feel that we are doing our part to improve telehealth by using our resources to help existing telemedicine providers and AI startups who are focused on leveraging AI for advanced telehealth applications.

For example, we recently had a client, a tech giant in the healthcare industry known for its telemedicine platform that connects providers, insurers, patients, and innovators to deliver greater access to more affordable, higher quality care. Due to the unprecedented times of the global COVID pandemic, this client needed to strengthen and expand their virtual care platform in order to stay ahead of their competition. We created a proprietary Accelerate Framework in order to meet aggressive deadlines and reduce the risk of market loss. Overall, upon implementation, the client saw three areas of improvement to make their application more competitive for their new market.

1. Improved access and documentation of Patient Care History
2. Migrating data and integrating old data from legacy systems
3. Increasing Security standards and SSO

What we did for them, we could do for you whether you have an existing telehealth application or are in the design and development phase; if you want to learn more about transforming your telehealth offerings, please contact us.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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How AI is Solving Healthcare Administrative Problems

In 2022 readers of these pages saw many reports on the incredible advances AI is creating in diagnostics and patient care. However, there is more to the delivery of healthcare in this country and to improving patient outcomes than direct treatment protocols. As it turns out, AI is tackling those issues as well, solving many of the bottlenecks and other burdens that are placed upon healthcare administration.

“Clinical burnout” is a very real problem among healthcare personnel. Mounds of paperwork and short staff have only increased these pressures in recent years. The more time doctors, nurses, and other clinical staff have to spend on administrative duties, the less time they can spend with patients – overall care at the facility or hospital suffers, and readmission rates increase.

According to the American Academy of Family Physicians, primary care physician appointments take an average of 18 minutes, of which 49% of the time is spent handling electronic health recording.

But a relatively new application of AI in healthcare, known as “computer-assisted physician documentation (CAPD),” can and is changing all of that, so more of the clinician’s time during a visit is spent on patient care and not on administrative tasks.

According to 3M when of the initial implementers of the solutions, “CAPD acts as a scribe and advisor, nudging clinicians with documentation suggestions to make record keeping as thorough as possible. These non-intrusive nudges decrease clinician stress and reinforce accurate billing and reimbursement.”

As AI assists with the capture-to-code process, integrated electronic health record (EHR) systems must work in tandem with cloud-based systems to pass and connect information across departments.

CAPD assistants not only save time but also lower the chances of errors and duplicative work. Information sharing across departments gives transparency to the revenue cycle and provides a complete picture of both the patient story and population health.

“The better the coding is, the better the outcome for the hospital, which enables the hospital to make decisions that will improve their services to patients,” explains Catalin Velescu, 3M area division director of the EMEA region.

How BigRio Helps Facilitate Advancement in Healthcare AI

Like the AI technology being developed and implemented by big IT players such as 3M, BigRio is also helping to foster innovation in AI for healthcare.

In fact, one of our most successful cases was using our resources to create a new cloud-based intuitive model for one of the top 10 EMR/HER providers in the US. The Client realized that their EHR platform needed UI/UX redesign and revision to take advantage of cloud-based integrations and applications. BigRio stepped in to create a modernization roadmap strategy, architecture, execution plan, and prototype to fit the Client’s needs.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the biomedical community.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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Artificial Intelligence Moves Heavily Into the NFT Space!

Investors take note, machine learning is beginning to have a powerful impact on generative art non-fungible tokens (NFTs).

NFTs are cryptographic assets on a blockchain with unique identification codes and metadata that distinguish them from each other. Most often, NFTs are used to represent real-world items like artwork and real estate. “Tokenizing” these real-world tangible assets makes buying, selling, and trading them more efficient while reducing the probability of fraud.

With that in mind, AI is becoming increasingly important in the non-fungible token space. “Generative art” – art that has been created by AI — has quickly emerged as one of the main categories of the NFT market, driving innovative projects and investment in astonishing collections. From the works of AI art legends such as Refik Anadol or Sofia Crespo to Tyler Hobbs’s new QQL project, NFTs have become one of the main vehicles to access AI-powered art.

The rise of generative AI has come as a surprise even to many of the early AI pioneers, who mostly saw this discipline as a relatively obscure area of machine learning. Its leap to dominance in the NFT market has largely been driven by gains in computational power and next-gen MI algorithms that can help models learn without requiring a lot of labeled datasets, which are incredibly limited and expensive to build.

One of the most significant of these advances has been “text to image” (TTI). AI-driven TTI programs such as DALL-E and GLIDE allow users to describe in text what they would like the program to render, and it then creates an interpretive image based on the text, with some profoundly remarkable results. Thus making TTI ideal for the creation of unique and marketable NFTs.

There are also similar generative art solutions such as “text-to-video” or “image-to-image,” but TTI, by far, is having the greatest impact on the NFT market because a disproportionate percentage of digital art collectibles are represented as static images.

Throughout the history of technology, there have been many examples of seemingly disparate trends coming together to form a market symbiosis that benefits both. The most recent example is the social-mobile-cloud revolution, in which each one of those trends expanded the market of the other two.

Generative AI and NFTs are starting to exhibit a similar dynamic. Both trends have been able to bring complex technology to mainstream culture. NFTs complement generative AI with digital ownership and distribution models that would be nearly impossible to implement otherwise. Similarly, generative AI is likely to become one of the most important sources of NFT creation now and into the future.

How BigRio Helps Facilitate Investment in AI Startups

Like what is occurring with NFT and AI-generated art, BigRio looks for and helps to facilitate such market symbiosis.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the growing AI investment community.

Because we see so many potential AI innovators, we are also ideally suited to create the kind of synergy between concepts and applications such as is occurring with AI, ML and NFTs.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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AI Leverages Nursing Expertise to Improve Patient Outcomes

The know-how and experience of nurses are a critical body of knowledge and expertise about patients and patient care. Wouldn’t it be wonderful if there was a way to pool all of that knowledge into one place for hospitals and health organizations to make better decisions about patients?

There is, and as you might imagine, it involves AI.

Several health systems, led by the Columbia University Irving Medical Center (CUIMC), are testing an AI-driven predictive tool that is attempting to emulate nurses’ seemingly innate ability to pick up cues about patients’ health from subtle changes in behavior and appearance.

According to its developers, CONCERN (COmmunicating Narrative Concerns Entered by RNs) is a predictive tool that extracts nurses’ expert and knowledge-driven behaviors within patient health records and transforms them into observable data that support early prediction of organ failure or other critical conditions in hospitalized patients.

CUIMC is partnering with three hospital systems — Mass General Brigham (MA), Vanderbilt University Medical Center (TN), and Washington University School of Medicine/Barnes-Jewish Hospital (MO) — to test the effectiveness of the CONCERN implementation toolkit, developed to support large-scale adoption of the tool.

This initiative recently received funding from the American Nurses Foundation through the Reimagining Nursing Initiative.

“CONCERN shows what nurses already know: Our risk identification is not simply a subjective clinical hunch,” said Sarah Rossetti, assistant professor of biomedical informatics and nursing at Columbia, in a statement. “We’re demonstrating that nurses have objective, expert-based knowledge that drives their practice, and we’re positioning nurses as knowledge workers with tremendous value to the entire care team.”

Annually, more than 200,000 patients die in US hospitals from cardiac arrest, and over 130,000 patients’ deaths are attributed to sepsis. Many of these deaths could be preventable if patients who are at risk are detected earlier. Prior work from the CONCERN team found that nursing documentation within EHRs contains information that could contribute to early detection and treatment, but these data are not being analyzed and exposed by EHRs to clinicians to initiate interventions quickly enough to save patients.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

Like the CONCERN project, leveraging human expertise and adapting to the predictive power of AI algorithms is an area where AI and machine learning are making one of the technology’s biggest impacts in the healthcare field.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve patient outcomes. In fact, it was my father’s own battle with and eventual death from lung disease that set me on my path to finding ways to use AI to provide earlier detection of serious medical conditions for improved patient care.

Eventually, among our other success stories, we did collaborate with a researcher who is in the process of developing a cognitive digital twin of the human lung. Right now, that technology is being used specifically in the realm of testing inhalers for asthma patients, but like the CONCERN project, it has broader implications for better diagnostics and early interventions to save lives.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the biomedical community.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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AI Creates Novel Proteins Paving the Way for Radical New Therapies!

An exciting partnership between computing and graphics giant Nvidia and AI startup Evozyne has announced that they have been able to produce novel versions of a human protein that has never been seen in nature — but with “enhanced function” and the same safety as native proteins. The researchers say that the AI breakthrough lays the groundwork for potential new therapies for rare disorders.

The collaborators say they developed the novel proteins by “listening to the language of life.”

Natural language processing, or NLP, is a cornerstone of AI programs. NLP is software that is designed to analyze language in any form, from handwritten notes to complex peer-reviewed papers. In healthcare, such NLP algorithms are being written that can analyze any kind of document and other datasets and identify biologically relevant text elements such as the names of genes, proteins, drugs, clinical manifestations of a particular disease, and anything else relevant to a given research team’s target.

Kimberly Powell, vice president of healthcare at Nvidia, says natural language learning techniques can also be applied to genomics, in particular proteins that are encoded by our genes.

“We’ve learned that these large language models can understand relationships just through studying amino acid sequence,” Powell said. “There is information about protein function when you can encode and represent and explore that data in these large language models.”

The results of the collaboration between Nvidia and Evozyne were announced during the recent J.P. Morgan Healthcare Conference in San Francisco. Powell discussed them during a separate briefing with journalists. Neither company develops new drugs, but their technologies are used by biotech and pharmaceutical companies working in drug discovery.

The two companies began working together in 2022, collaborating to develop a new deep-learning model that can learn the rules of protein function. Using those rules, they aimed to design new proteins with improved functions. The model was built on Nvidia’s technology for training and deploying large language models for biology.

When engineering therapeutic proteins, scientists aim to make changes that enhance the protein’s function without compromising its safety. In the research described by Nvidia, Evozyne was able to create a protein with 51 mutations. Despite all of those changes, that protein was still able to achieve a two-and-a-half times enhancement in functionality compared to the native human protein on which it was modeled.

In this case, the protein model was specifically designed to test novel therapeutics for a rare condition known as phenylketonuria (PKU), in which phenylalanine levels build up in the body and cause neurological impairment because individuals with the condition cannot process phenylalanine, an amino acid found in certain foods.

Right now, there are few drugs available to treat PKU, and those with the condition must be on strict diets avoiding foods that contain phenylalanine.

How BigRio Helps Facilitate Investment in AI Startups

Much like the collaboration between Nvidia and Evozyne, BigRio is partnering with startups to develop healthcare solutions with AI at the core of their solutions and our sister company Citadel Discovery was launched in 2021 with the purpose of giving a kind of “open access” to the data and technology that will drive the future of pharma research streamlining and lowering the costs of drug discovery and biological research.

We have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:
• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
• Assistance in the development and testing of the MVP, Prototypes, and POCs.
• Professional services for implementation and support of Pilot projects
• Sales and Marketing support and potential client introductions.
• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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