Accelerates development of personalized cardiac AI on the HeartBeam platform for wellness and clinical applications, including assessing heart attack risk ・Combines Mount Sinai’s world-class AI and ...

This useful study supplements previous publications of willed attention by addressing a frontoparietal network that supports internal goal generation. The evidence is solid in analyzing two datasets ...

Behavioral changes—such as anxiety, depression, irritability, apathy or agitation, collectively known as neuropsychiatric ...

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Scientists usually study the molecular machinery that controls gene expression from the perspective of a linear, two-dimensional genome—even though DNA and its bound proteins function in three ...

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Myocardial ischemia, the primary driver of heart attacks, remains the leading cause of death and disability worldwide. Delays in diagnosis directly correlate with increased myocardial necrosis, higher ...

Texas Instruments MSPM0G5187 and AM13Ex are two new microcontroller (MCU) families featuring the company's  TinyEngine neural processing unit (NPU) to ...

HeartBeam (NASDAQ:BEAT) announced a strategic collaboration with the Icahn School of Medicine at Mount Sinai aimed at accelerating the development and clinical validation of next-generation artificial ...