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The development of predictive AI tools in healthcare shows tremendous promise in accelerating more accurate diagnoses and improving the safety and quality of healthcare. However, what’s been lacking is a standard way to evaluate whether or not an AI tool will do what it says it...

Clinical AI can reduce harm, improve patient outcomes and deliver financial benefits by augmenting physician and nurse decision-making at the bedside, making care more proactive. But, knowing where to begin can be tricky. In what clinical areas should your health system consider applying AI? With...

Building and deploying AI predictive tools in healthcare isn’t easy. The data are messy and challenging from the start, and building models that can integrate, adapt, and analyze this type of data requires a deep understanding of the latest AI/ML strategies and an ability to...

Though predictive tools are widely used in the healthcare setting, there are no official rubrics or guidelines for evaluation or requirements for consistent regulatory oversight. But, what can often happen during deployment is something called “dataset shift.” Dataset shift occurs when a tool “underperforms because...

Bayesian Health's platform drove faster treatment for sepsis, with high provider adoption. A large, five site study analyzing use and practice impact over two years for Bayesian Health’s sepsis module showed high sensitivity (80%+) with high precision (1 in 3 alerts were provider confirmed). Sepsis...

Today, Bayesian Health exited stealth mode, bringing to market its research-backed AI platform that helps health systems deliver safer and higher quality care. But we’ve been at it for much longer—we’ve been heads down, working as a company for more than three years.  Why did we...

Several years ago, I lost my nephew to sepsis -- he was only 26 years old when this happened. It was devastating for my family. Sepsis is a life-threatening syndrome that is preventable only when it's recognized early and treated in a timely way. Unfortunately,...

As health systems look to adopt new technology platforms that engage frontline caregivers to improve patient outcomes, understanding how a platform interacts with users and sustains engagement is critical to understanding if the technology will be successful. Even the very best solutions won’t have any...

When building healthcare AI / predictive tools in the real world, certain issues should be considered and accounted for, such as understanding how the tool generalizes from one site to another, how it stands up to changes in physician practice patterns, and how sensitive it...

Dr. Suchi Saria shares her journey bringing machine learning to the bedside, overcoming barriers, and creating practical applications that impact real patients.   Watch the TedMed talk here.    ...

Dr. Suchi Saria discusses the development and outcomes of her early sepsis warning system, TREWS, and a call to action for industry experts and policymakers in this TEDx talk.   Watch the TedTalk here.    ...

Forbes named Dr. Suchi Saria one of 20+ brilliant women achieving incredible impact in artificial intelligence in 2017, based on her work collecting data from sensor platforms and electronic medical records to improve healthcare delivery.   Read the full profile here.    ...

WebMD features Dr. Suchi Saria in a discussion on how artificial intelligence works, the benefits of using AI in healthcare, and the role it will play (and won’t play) in the future of healthcare delivery.   See the full video here.    ...

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