A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.
LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...
The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...
How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by ...
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Machine learning detects early brain changes linked to Alzheimer's disease
Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer's disease with nearly 93% accuracy.
Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...
Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?
Santa Clara, CA / Syndication Cloud / March 3, 2026 / Interview Kickstart The rapid acceleration of AI adoption across ...
MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
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