Tag Archive for: #adoption

The 4 Trends Driving Health AI Platform Adoption

8/03/22 MIT: Sloan Management – The 4 Trends Driving Platform Adoption in Health Care

Health care has been slow to adopt platforms. But investment, the threat of competition, and the potential to save lives is pushing the industry forward. The combination of activity from big tech and a government mandate has also had a trickle-down effect on digital health platform startups, which are making their data available using FHIR APIs, said Suchi Saria, Ph.D., founder and CEO of AI platform Bayesian Health.

“Five years ago, this was extremely hard. Now, you can engage with multiple partners to connect and meaningfully stitch data together and build high-quality information out of it,” she said. “It’s an enormous opportunity for using the right kind of machine learning tools to learn from messy data sets. Instead of traditional experiments in the lab, you’re able to learn in the wild.”

LINKS

Read the MIT article

Read more about Bayesian Health’s approach to Adaptive AI

Algorithm That Detects Sepsis Cut Deaths by Nearly 20 Percent

08/01/22 Scientific American – Algorithm That Detects Sepsis Cut Deaths by Nearly 20 Percent

Detecting sepsis earlier with Bayesian’s health AI. “I think that this model for machine learning may prove as vital to sepsis care as the EKG [electrocardiogram] machine has proved in diagnosing a heart attack,” says Karin Molander, who is an emergency medicine physician and chair of the nonprofit Sepsis Alliance. “It is going to allow the clinician to go from the computer…, trying to analyze 15 years’ worth of information, to go back to the bedside and reassess the patient more rapidly—which is where we need to be.”

LINKS:

Read the Scientific American article

Learn more about Bayesian’s peer-reviewed research on sepsis here

New AI System Developed That Can Quickly Pinpoint Sepsis Occurrence

7/28/22 Gilmore Health News – New AI System Developed That Can Quickly Pinpoint Sepsis Occurrence

Saria and the team of other researchers at John Hopkins hospital built the Targeted Real-Time Early Warning System – the AI system that can detect the symptoms of sepsis early in patients by combining their medical history with existing symptoms, plus their lab results and revealing to doctors if there is a possible risk for sepsis. This machine-learning system also suggests treatment procedures, which may be administering antibiotics.

LINKS

Read the Gilmore Health News article

Read more about Bayesian Health’s approach to Adaptive AI

This AI saved hundreds of lives from sepsis in just five hospitals

07/26/22 – ZME Science – This AI saved hundreds of lives from sepsis in just five hospitals. Across the US, thousands more could be spared Lowering sepsis risk using Bayesian’s adaptive AI.

Thanks to this system, the patients were 20% less likely to die of sepsis, potentially saving thousands of lives across the U.S. if it is implemented nationwide. About 1.7 million American adults develop sepsis, and more than a quarter million die because of it.

LINKS:

Read the ZME article

Learn more about Bayesian’s peer-reviewed research on sepsis here

AI-Driven Clinical Sepsis Screening Approach Demonstrated to Save Lives

07/25/22 Inside Precision Medicine – AI-Driven Clinical Sepsis Screening Approach Demonstrated to Save Lives

Reducing sepsis mortality using Bayesian’s machine learning system. An adaptive artificial intelligence (AI) technology called the Targeted Real-time Early Warning System (TREWS) developed by Bayesian Health has shown its ability in a clinical setting to be an effective early warning screening tool for patients with sepsis. Detailed in three separate studies published in Nature and npj Digital Medicine, researchers from Bayesian and Johns Hopkins University demonstrated that deployment of the AI-driven clinical sepsis screening approach reduced mortality, morbidity, and length of stay of hospital patients. Importantly, the studies show timely use of Bayesian’s AI platform is associated with a relative reduction in mortality of 18.2% in sepsis patients.

 

LINKS

Read the IPM article

Learn more about Bayesian’s peer-reviewed research on sepsis here

Decreasing sepsis risk using Bayesian’s machine learning solution

07/25/22 Politico: Digital Future Daily – Applied AI Feature: Decreasing sepsis risk using Bayesian’s machine learning solution

Crucially, Bayesian Health’s AI is good not just at spotting sepsis cases, but also at avoiding false positives. That means that doctors ended up responding to nearly 90 percent of the alerts given, an especially important finding given high-profile cases like that of the health software giant Epic, whose sepsis model was found last year in a study to have accurately identified just a third of sepsis patients and produced a massive number of false alarms — something Steven Lin, executive medical director of Stanford’s Healthcare AI Applied Research team, told Ruth was a “wake up call” for both the health care and AI industries.

LINKS

Read the Politico article

Learn more about Bayesian’s peer-reviewed research on sepsis here

Groundbreaking results reveal AI can reduce sepsis deaths

07/25/22 HealthTech World – Groundbreaking results reveal AI can reduce sepsis deaths

Peer reviewed research shows drop in sepsis death. Unlike traditional AI that follows a “one-size-fits-all” approach to patients and hospitals, Bayesian’s adaptive approach to AI takes into consideration the diversity of the patient population.

 

LINKS

Read the HTW article

Learn more about Bayesian’s peer-reviewed research on sepsis here

Modern Healthcare: AI can reduce sepsis-related deaths, study shows

07/22/22 Modern Healthcare – AI can reduce sepsis-related deaths, study shows

Bayesian helps hospitals reduce sepsis mortality. Using artificial intelligence and a machine learning system, providers were able to diagnose and treat cases of sepsis earlier than with traditional methods, decreasing sepsis patient mortality by nearly 20% according to new research.

LINKS

Read the Modern Healthcare article

Learn more about Bayesian’s peer-reviewed research on sepsis here

AI Shows Potential to Reduce Sepsis Deaths

07/21/22 STAT – Serving as a ‘clinical colleague,’ AI shows potential to reduce sepsis deaths in real-world studies

Reducing sepsis death through Bayesian’s machine learning solution. “The most effective tools will be those that enhance, rather than try to replace, the capabilities of bedside clinicians: those that turn a large volume of data and information into actionable knowledge and wisdom””

LINKS

Read the STAT article

Learn more about Bayesian’s peer-reviewed research on sepsis here

Real-time early warning system for sepsis

07/21/22 NATURE MEDICINE – A real-time early warning system for sepsis detection shows promising adoption by healthcare providers and important improvements in patient outcomes.detection shows promising adoption by healthcare providers and important improvements in patient outcomes.

Sepsis is a notoriously difficult condition to manage, mainly because of challenges with its early detection, and it continues to have a high mortality rate; a recent meta-analysis reported a pooled 30-day rate of 24%. Sepsis can develop outside or inside the hospital, on general care units or in the ICU — in one study, 41% of cases occurred outside the ICU, where patients are less closely monitored.

LINKS

Read the NATURE MEDICINE editorial

Learn more about Bayesian’s peer-reviewed research on sepsis here

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