As a patient recovers from a wound, a doctor may watch over them, monitoring the healing process and prescribing treatments based on the body's responses. But a wide variety of factors including diet, ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
The adoption of machine learning approaches in systematic reviews is fundamentally transforming evidence-based medicine. Traditionally, systematic reviews have involved painstaking manual screening of ...
Models built on machine learning in health care can be victims of their own success, according to researchers at the Icahn School of Medicine and the University of Michigan. Their study assessed the ...
The team utilized machine learning to analyze public data from the National Health and Nutrition Examination Survey.
"Both studies emphasize our unique approach to using machine learning and big data in academic medicine," said Jason Moore, Ph.D., professor and chair of the Department of Computational Biomedicine at ...
A multi-institutional research team has demonstrated how artificial intelligence and machine learning can optimize therapy selection and dosing for septic shock, a life-threatening complication that ...
Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...
Researchers at the University of Toronto say they have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine ...
In an editorial, Monica M. Bertagnolli assesses the promise of artificial intelligence and machine learning (AI/ML) to study and improve health. The editorial was written by Dr. Bertagnolli in her ...
Privacy-preserving AI technique enables researchers to improve cancerous brain tumor detection by 33%. SANTA CLARA, Calif.--(BUSINESS WIRE)--What’s New: Intel Labs ...