Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.

Researchers have developed an AI-guided, shape-changing microneedle patch that speeds wound healing while reducing infection ...

Chronic wounds remain a major health care challenge, especially for people with diabetes, who often experience delayed ...

Chronic wounds remain a major healthcare challenge, especially for people with diabetes, who often experience delayed healing ...

Smartwatches may transform blood sugar tracking, but today’s advances depend on CGMs, AI, and regulated health tech ...

The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...

The box from the Finnish company MedicubeX is now being used in various care scenarios. In an interview with heise online, founder and CEO Vili Kostamo discusses the company's latest projects, ...

“This PIC Packaging Center of Competency at C2MI, launched in collaboration with Aeponyx and our partners, helps turn advanced integrated photonics into repeatable, industrial-grade capabilities in ...

Cedars-Sinai Health Sciences University investigators developed an AI-based model that can identify hospitalized patients at ...

A comprehensive review recently published in Current Molecular Pharmacology (2026, Volume 19, Pages 85–96) examines the ...