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 ...
A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.
Smartwatches may transform blood sugar tracking, but today’s advances depend on CGMs, AI, and regulated health tech ...
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, ...
The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...
“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 ...
Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...
A comprehensive review recently published in Current Molecular Pharmacology (2026, Volume 19, Pages 85–96) examines the ...
The Forecast 2026 project pits soccer fans against AI and statistical models to see who predicts the 2026 World Cup match ...
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