Tag Archive for: #sepsismortality

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

AI Offers Hope in Reducing Sepsis Deaths

07/21/22 Politico – Artificial Intelligence Offers Hope in Reducing Sepsis Deaths

Interesting article from Politico about Bayesian Health AI technology’s ability to detect sepsis earlier. “There are very few studies that have looked at actual outcomes post deployment of a model like this,” said Steven Lin, executive medical director of Stanford’s Healthcare AI Applied Research team. “They looked at adoption and what actually made it work — not just that it did work, but how did it work.”

LINKS

Read the Politico article

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

Bayesian Health and Johns Hopkins University Announce Ground-Breaking Results

07/22/22 AI Thority – Bayesian Health and Johns Hopkins University Announce Ground-Breaking Results With a Clinically Deployed Artificial Intelligence Platform

New health AI system from Bayesian detects sepsis earlier.  Where Early AI Deployments Have Failed to Produce Real-World Results, Bayesian Demonstrates Reduced Mortality, Long-Term Efficacy, High Adoption and Fewer False Alerts in a Trio of Prospective, Peer-Reviewed Studies

LINKS

Read the AI Thority article

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

Suchi Saria Named Finalist for AIMed AI Champion Award

05/26/22 Suchi Saria Named Finalist for AIMed AI Champion Award

SAN FRANCISCO, CA— AIMed have announced the finalists for this year’s AI Champions Awards, which will take place on Wednesday May 25 as part of the live AIMed Global Summit in San Francisco, CA.

“This is all about recognizing some of the great people and organizations that are helping to drive the agenda for artificial intelligence in healthcare”, said AIMed founder Anthony Chang. “Our finalists have worked tirelessly to deliver some incredible outcomes, and they are fully deserving of the accolades. We look forward to meeting them all in person in California in May.”

AI Champion Non-clinician 2022

  • Cansu Canca, Director, AI Ethics Lab
  • Fei-Fei Li, Sequoia Capital Professor of Computer Science, Stanford University
  • Alfonso Limon, Chief Liaison of Research and Development, Oneirix
  • Suchi Saria, Director, Research and Technical Strategy, Malone Center for Engineering in Healthcare, Johns Hopkins
  • May Wang, Director of Biomedical Big Data Initiative, Georgia Tech

LINKS

Read the Press Release

Read more about Bayesian Health’s approach to Adaptive AI

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