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Logistic regression is considered a type of supervised machine learning algorithm. Advantages of the method in this setting include that it is interpretable, simple to understand and can be ...

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 ...

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

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 ...

Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

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 ...