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A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.

This study examined whether machine learning could predict the risk and contributing factors of no-shows and late ...

Journal Reference: Eri Shimono, Katsuya Inoue, Takio Kurita, Yoji Ichiraku. Logistic regression analysis for the material design of chiral crystals. Chemistry Letters, 2018; DOI: 10.1246/cl.171233 ...

EHR data may be particularly suitable for machine learning (ML) techniques, as such algorithms can process high-dimensional data and capture nonlinear relationships between variables. By comparison, ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

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 ...