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.

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

Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer's disease with nearly 93% accuracy.

Feasibility and Implementation of a Digital Health Intervention Electronic Patient-Reported Outcomes–Based Platform for Telemonitoring Patients With Breast Cancer Undergoing Chemotherapy Among the 76 ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Understanding and preventing drug side effects holds a profound influence on drug development and utilization, profoundly impacting patients’ physical and mental well-being. Traditional artificial ...

A new review highlights how machine learning is transforming the way scientists detect and measure organic pollutants in the ...

Performance evaluation of an AI-powered system for clinical trial eligibility using mCODE data standards. ATheNa-Breast: A real-world pilot of an artificial intelligence (AI) chatbot using therapy ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Prospect Prediction Markets Inc. (TSXV: MKT) (OTCID: MKTSF) (FSE: DEP) ("Prospect Markets" or "Prospect" or the "Company") is pleased to announce ...