This is the largest real-world analysis of mycophenolic acid in pediatric lupus nephritis to date, providing a decision-support system to help balance efficacy and safety.
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.
More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from causes other than cancer relapse. Those numbers capture the uneasy truth of ...
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 ...
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising new medicine. Normally, creating better ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Thirty-day mortality of patients with major trauma fell if they received intubation before hospital admission per prediction from a machine learning risk-stratifying model, according to data published ...
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Improving AI models' ability to explain their predictions
In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...
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