Introduction We aimed to determine the association between paternal labour migration and the growth of the left-behind ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Background Prehospital delays remain critical barriers to timely acute coronary syndrome (ACS) care, particularly for ...

Abstract: The logistic regression model is a linear model widely used for two-category classification problems. This report examines the enhancement and improvement methods of logistic regression ...

Background: Patients with persistent atrial fibrillation (PsAF) exhibit a high recurrence rate following catheter ablation, and there is a lack of individualized prediction tools based on clinical ...

Singapore’s national AI program has moved its Sea-Lion large language model off Meta’s model family and adopted Alibaba Cloud’s Qwen architecture, according to information cited by foreign media from ...

Nov 10 (Reuters) - Tesla's (TSLA.O), opens new tab best-selling Model Y's program manager, Emmanuel Lamacchia, announced his departure on Sunday after nearly eight years, marking another high-profile ...

We should add a linear classifier (logistic regression style) as an alternative to the current MLP in patient-level modeling. Same input format and preprocessing as MLP (patient feature vectors).

1 Clinical Laboratory, Dongyang People’s Hospital, Dongyang, Zhejiang, China 2 Clinical Laboratory, The Second People’s Hospital of Yuhuan City, Yuhuan, Zhejiang, China Introduction: In this study, we ...

ABSTRACT: There is a set of points in the plane whose elements correspond to the observations that are used to generate a simple least-squares regression line. Each value of the independent variable ...

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 ...