Tag Archive for: AI

Startup Leverages AI to Challenge Google for Search Engine Supremacy!

Search engine technology startup You.com has announced the launch of YouChat 2.0, a groundbreaking new “multimodal conversational AI” system that the company says will take the internet search experience to “a whole new level,” leaving search engine giant Google wondering what happened!

The company says that YouChat 2.0 is the first web search that combines advanced conversational AI with community-built apps, offering a unique and interactive experience with each query. Its blended large language model, known as C-A-L (Chat, Apps, and Links), serves up charts, images, videos, tables, graphs, text, or code embedded in its responses to user queries. The idea is fewer open tabs and less drifting away from your search engine.

“We already have 150+ apps in our main search results page, but we’re now pulling more into the chat world and into this chat interface, which is non-trivial because you basically have to allow the chat model to decide when is best to answer a question by just showing you the facts,” said You.com co-founder and CEO Richard Socher in an interview with VentureBeat. “No one has done this yet — we’re the first to launch it to the world publicly.”

Socher knows a thing or two about groundbreaking advances in natural language processing (NLP), the technology that underpins all popular search engines. According to Google Scholar, Socher is currently the fourth most cited researcher in the field. As former chief scientist (and EVP) at Salesforce and former adjunct professor at Stanford’s computer science department, Socher has built his career on novel NLP applications. He now thinks it’s time to reimagine the way we interact with traditional search engines.

“Google has done incredible research and propelled the field forward in many dimensions in terms of its research, but they are making $150 billion a year by invading your privacy and showing you ads on a search results page,” Socher said, appearing visibly frustrated with the current state of affairs. “So when you develop technology, that would work great if, instead of six ads, you had one ad, but [if] it means you lose $500 million a day, you’re probably not incentivized to launch that new technology into the world.”

“It’s the classic innovator’s dilemma,” he added. “Google is very good at running things not profitably for a long time, like Maps and YouTube, and then pulling ads into it. The problem is this particular technology changes their core product.”

The company invites developers to submit apps to its open platform and work together to create the ultimate chat-search-do engine. Developers can learn more at You.com’s developers page.

How BigRio Helps Bring Advanced AI Solutions to the Internet Experience

The announcement of YouChat 2.0 by You.com is yet another example of how innovative startups are advancing the ubiquity of AI and NLP. AI algorithms are already “running behind the scenes” of most of our internet and social media experiences, and soon they will be little or no separation between Internet of Things applications, chat, and AI, with one very much totally reliant on and integrated with the other.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve the digital 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 the Internet of Things 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.

New AI Solution Uses Pooled Data for More Advanced Automotive Diagnostics

Protech Automotive Solutions’ ID3 solution leverages the idea that many data points are necessary to achieve the most accurate calibrations for automotive safety features that often need to be recalibrated after a vehicle has been involved in a collision.

ID3, which is pronounced “I-D cubed,” was recently unveiled at the 2022 SEMA Show. It uses proprietary artificial intelligence and machine learning algorithms to identify calibration needs for a given automotive repair after a vehicular collision. While that service exists in many forms today, Protech Vice President of Product Development Don Mikrut says that the key difference with ID3 is that instead of merely returning what kind of calibrations might be needed, ID3 is able to use its knowledge base to deliver more accurate assessments almost instantaneously.

“We start to triangulate all that data through the algorithms and the machine learning that we’ve developed, to come back and say, based on your pre-scan, and the estimated damages, and the OE procedures and knowledge base, we’ve been able to triangulate this,” says Mikrut, hinting at the source of the three in ID3’s name. “Every line of that estimate comes back and tells you this is what needs to be calibrated on this vehicle based on the damages.”

And according to Mikrut, all of that happens in “milliseconds.”

The genesis of the development of the ID3 AI solution was driven by all of the new safety features, such as autobraking and proximity sensors and others that are known as ADAS, for Advanced driver-assistance systems. With the advent of ADAS systems, collision shop owners had to devote a significant amount of time to manually research and determine which ADAS systems needed to be recalculated and how to do so. Existing diagnostic scans could reveal what systems were present on the vehicle but not necessarily which ones were impacted by the collision, which left a process that was open to interpretation and judgment calls by repair techs.

ID3 was developed to solve this issue.

The team at Protech leaned on “30-plus years of building a knowledge base,” according to Mikrut, that encompasses Protech’s acquired expertise as well as data from OEs for ID3 to draw on.

The solution was rolled out in 2022, and as of the start of this year, it is being used in over 1200 locations.

“ADAS ID3 builds on our expertise and history in the vehicle diagnostic industry by revolutionizing the identification of calibration and repair needs, thus saving our technicians and partners time and money,” said Chris Gutierrez, Vice President of Technology Innovation, who led the products development team. “Protech’s focus is to fix vehicles the right way the first time.”

AI, the Auto Industry. and CarTwin

Just as ID3 is leveraging AI to advance vehicle diagnostics and repair calibrations, digital twin solutions like those developed by CarTwin are also taking predictive maintenance to new levels all across the transportation industry.

Digital twin technologies extend the lifespan of cars and other vehicles by monitoring the vehicle’s “health” through its “digital twin.”

Basically, CarTwin can provide diagnostic and predictive models for all vehicle systems for which data is available (either directly or indirectly) onboard the vehicle.

Virtually any part of the vehicle that has sensors or that sensors can be developed for can be “twinned.” These data sets are then enhanced and augmented with design and manufacturing data that is already available by the OEM.

Primarily designed for use in fleets of vehicles, in combination with powerful AI models, CarTwin predicts breakdowns, monitors and improves performance, and measures and records real-time greenhouse gas emissions, which reduces expensive maintenance costs and avoids lost revenue associated with fleet downtime.

It is very likely in the not-too-distant future, ADAS-type technologies will advance to the point where fully autonomous vehicles will replace human-driven fleets of over-road cargo transportation and taxis and limousine services. No doubt, technology such as CarTwin’s will also be incorporated into the algorithms to keep these self-driving vehicles not only safe but on the road longer.

Rohit Mahajan is a Managing Partner at BigRio and the President and Co-Founder of Citadel Discovery. He has a particular expertise in the development and design of innovative AI and machine learning solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

CarTwin has leveraged AI and Digital Twin technologies to create a digital, cloud-based clone of a physical vehicle designed to detect, prevent, predict, and optimize through AI and real-time analytics. 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.

 

Can AI Be Used to Predict Suicide Risk?

There has been no lack of news about how AI is redefining healthcare and improving patient outcomes for physical ailments. There has not been that much news, however, on how AI can help in the treatment of emotional or mental disorders.

Until now.

Researchers have just released the results of a study in which they used AI to better predict suicide risk.

The scientists from Worcester Polytechnic Institute (WPI) and Harvard Medical School-affiliated McLean Hospital in Belmont conducted a study assessing the use of AI to predict and gain a better understanding of suicide and the mechanisms and emotional states that drive self-injury.

This particular study targeted women because, according to the CDC, death by suicide is increasing at an alarming rate among women. The group of researchers developed an algorithm that was designed to predict suicide attempts among participants and identify subgroups of patients who were at the highest risk of entering a suicidal mindset.

They then used AI approaches to cluster data to expose any existing patterns. The patterns revealed a broad set of dissociative symptoms, such as the lack of connection between one’s sense of self and the environment. This was often due to trauma, the researchers said.

Following this step, researchers trained an algorithm to distinguish between patients with various dissociation levels and the 30 healthy controls. They found that this tool could zero in on specific dissociative symptoms, predicting previous suicide attempts with an accuracy of nearly 90% percent.

Aside from AI being able to predict thoughts of self-harm and previous suicide attempts accurately, researchers also noted that the study emphasized the need for clinicians to assess patients for dissociative disorder symptoms.

“We’re trying to say that among these hundreds of symptoms and indicators, our results suggest these two or three symptoms may be helpful to focus in on,” said Dmitry Korkin, Ph.D., the Harold L. Jurist ’61 and Heather E. Jurist Dean’s Professor of Computer Science at WPI, one of the lead researchers on the project.

The key takeaway from this study is that it is one of the first to show that AI-driven programs can give clinicians predictive and theoretically preventive tools for mental illnesses, just as they are already doing in practice for many physical disorders.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

The WPI research is one of the few studies that are now showing that AI has predictive value in mental health, just as it has already been put into practice in improving physical conditions. In fact, improving disease detection and diagnostics – whether that be physical, and now we see mental health — is the area where AI is making one of the technology’s biggest impacts.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve diagnostics.

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.

You can read much more about how AI is redefining healthcare delivery and drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.

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.

 

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.

 

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.

 

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.

 

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.

 

Microsoft Partners to Develop AI-Based Healthcare Services

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.

 

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.

 

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.