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 ...
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 CT-based whole-lung radiomic nomogram accurately identifies AECOPD and offers a robust tool for clinical diagnosis and treatment planning.
A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...
Joint components contributed substantially to model performance, while distinct components captured phase-specific variations.
This is a preview. Log in through your library . Abstract We derive the exact formula linking the parameters of marginal and conditional logistic regression models with binary mediators when no ...
Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.
Among adolescent girls with concussion, greater initial emotional symptom severity, reflected in higher anxiety, depression, and sleep disturbance scores, was associated with a higher likelihood of ...
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