The team utilized machine learning to analyze public data from the National Health and Nutrition Examination Survey.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

What actually happens inside the brain when learning works? Drawing on neuroscience, this breakdown of Stanislas Dehaene’s 'How We Learn' explains attention, error, practice, sleep, and motivation, ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.

Heart specialists at Mayo Clinic today presented new research at the 2026 Society of Thoracic Surgeons Annual Meeting that ...

Overview: AI helps farmers make accurate decisions using real-time data from soil, weather, and crops.Precision farming ...

Clinical and health care resource use burden were greater among patients with diagnosed hypereosinophilic syndrome or predicted hypereosinophilic syndrome via machine learning vs. those without the ...

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...

Google DeepMind released AlphaGenome on January 28, an AI model that predicts how DNA sequences translate into biological functions, processing up to one million base-pairs at once and outperforming ...

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 ...

Artificial intelligence has moved from crunching physics data in the background to actively proposing new theories and ...