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.
Machine learning predicts who will decline faster in Alzheimer’s disease using routine clinic data
Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
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.
Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
New book explains how AI and machine learning are transforming banking through fraud detection, credit risk modeling, ...
The DNA foundation model Evo 2 has been published in the journal Nature. Trained on the DNA of over 100,000 species across ...
Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new physical understanding.
A new review highlights how machine learning is transforming the way scientists detect and measure organic pollutants in the ...
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