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There are dozens of machine learning algorithms, ranging in complexity from linear regression and logistic regression to deep neural networks and ensembles (combinations of other models).

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

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, ...

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 ...

Researchers at Pennsylvania State University examined whether machine learning could predict the risk and contributing ...

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 ...