New guidance from the World Health Organization outlines how stakeholders can ensure the appropriate use of large multi-modal AI models in healthcare. - bit.ly/3Ss0gJr

Cedars-Sinai’s Molecular Twin Precision Oncology Platform has outperformed the only FDA-approved test to predict pancreatic cancer survival. - bit.ly/42ryGjf

A machine learning model outperformed standard tools for predicting death and other serious complications in patients undergoing percutaneous coronary intervention. - bit.ly/3SvYd7l

Research findings from Cleveland Clinic and IBM demonstrated how AI models can better show how immune systems recognize threats, which may improve immunotherapies. - bit.ly/3vQJLOn

UC San Diego Health’s artificial intelligence tool to predict sepsis infection risk in emergency department patients has reduced mortality by 17 percent. - bit.ly/3OmZjjd

Researchers leveraging a machine learning-based “fragmentomics” approach may be able to detect cancer sooner using smaller blood samples than traditional methods. - bit.ly/3vQ4py2

New Deloitte survey suggests that healthcare leaders must focus on data, governance, consumers, and the workforce to successfully implement generative AI. - bit.ly/48PQLts

Clinical decision support tools can provide actionable information, but issues like alarm fatigue can increase clinician burnout. - bit.ly/3ug7kzI

Predictive analytics can enhance healthcare by supporting clinical decision-making, guiding population health management, and advancing value-based care. - bit.ly/3SoIupo

University of California San Diego researchers argue that healthcare AI regulations should require developers to demonstrate how these tools impact patient outcomes. - bit.ly/42zab3F

The eXtended-Reality Artificially Intelligent Ally combines generative AI and virtual reality to provide patients with self-administered, conversational therapy. - bit.ly/48g4wAo

New Center for Connected Medicine report highlights that oversight of artificial intelligence tools is of growing interest to healthcare executives. - bit.ly/3UJDC0O

Provider organizations play a key role in suicide prevention, and one health system shows how effective risk stratification can drive these efforts. - bit.ly/49FM4Cv

Novel deep learning model leverages metabolic biomarkers to predict the likelihood that Alzheimer's disease will develop long before clinical symptom onset. - bit.ly/3uGzeVS

New study suggests that the Epic Sepsis Model may only identify some high-risk patients after sepsis is clinically recognized, rather than before infection onset. - bit.ly/3UQrNWR