QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.

In a recent study published in Scientific Reports, researchers showed that a simple string-pulling task could help make a reliable assessment of shoulder mobility across animals and humans. Across ...

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 ...

Researchers used advanced machine learning to increase the accuracy of a national cardiovascular risk calculator while preserving its interpretability and original risk associations. Risk calculators ...

CAMBRIDGE, Mass.--(BUSINESS WIRE)--Iterative Health, a healthcare technology and services company partnering with physicians to advance gastrointestinal care, will present five abstracts at the ...

Nursing homes (NHs) using the Preferences for Everyday Living Inventory (PELI-NH) to assess important preferences and provide person-centered care find the number of items to be a barrier to using the ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

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 ...

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking ...