Researchers conducted a review of studies on AI use in oncology nursing to determine its potential role in clinical practice.

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Please provide your email address to receive an email when new articles are posted on . AI and machine learning are becoming household terms. Anyone who invests in the U.S. stock market is familiar ...

A novel machine learning version of the Opioid Risk Tool provides high precision screening for opioid use disorder in chronic pain patients.

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from ...

Depression and anxiety have been well documented in people with multiple sclerosis (MS), but often are undiagnosed or untreated. A machine learning model may help by analyzing routinely collected ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Research indicates that repetition and distributed practice effectively fires and rewires the brain, thereby strengthening memory and improving learning potential. This approach aims to develop and ...