Objective To develop prediction models for short-term outcomes following a first acute myocardial infarction (AMI) event (index) or for past AMI events (prevalent) in a national primary care cohort.
Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
TRAIL Score: A Simple Model to Predict Immunochemotherapy Tolerability in Patients With Diffuse Large B-Cell Lymphoma We trained models using logistic regression (LR) and four commonly used ML ...
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Smartphone motor tests can predict dopamine deficiency in Parkinson’s disease without brain scans
Researchers explore the use of smartphones coupled with clinical scores to evaluate motor function and predict dopamine ...
WHEN I WAS diagnosed with lymphoma 11 years ago, I was eager to learn my prognosis. As a graduate student, I had excellent electronic access to the medical literature and was quickly able to review ...
A tool that incorporates five predictors helps accurately identify patients with dermatomyositis who have an increased likelihood of concomitant cancer and can be used to help with early detection.
Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...
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