Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

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 ...

The workflow illustrates data acquisition from wearable sensors, hierarchical temporal feature extraction at multiple granularities, multimodal alignment with clinical text knowledge, and dual-task ...

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 ...

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 ...

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.

Rapid advances in artificial intelligence, machine learning, and data-driven computational modeling have opened unprecedented opportunities to transform ...

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 ...