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 ...

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort ...

Logistic regression is one of many machine learning techniques for binary classification -- predicting one of two possible discrete values. An example is predicting if a hospital patient is male or ...

急性胰腺炎（AP）致死率高且缺乏精准预后工具。本研究针对 AP 患者 30 天 mortality 风险，利用 LASSO logistic regression 筛选出年龄、APTT、DBIL 等 6 个独立预测因子，构建 nomogram 模型（AUC=0.862），经 DCA 验证具临床价值，为早期风险分层提供新工具。 急性胰腺炎（Acute ...

Dr. James McCaffrey of Microsoft Research says the main advantage of scikit is that it's easy to use (even though most classes have many constructor parameters). Logistic regression is a machine ...

Multicenter Phase I/II Study of Cetuximab With Paclitaxel and Carboplatin in Untreated Patients With Stage IV Non–Small-Cell Lung Cancer Data from 1,066 patients recruited from nine European centers ...