We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of ...
Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...
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.
The probability of disease development in a defined time period is described by a logistic regression model. A model for the regression variable, given disease status, is induced and is applied to ...
The researchers argue that their findings, published in Scientific Reports, could help clinicians anticipate which patients ...
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Early warning for diabetes: AI model identifies prediabetes risk with high accuracy
A Scientific Reports study developed a pattern neural network that integrates total antioxidant status with clinical and ...
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