Objective: To understand patient portal engagement stratified by patient characteristics among adults 50 years and older with at least 1 common chronic medical condition using electronic health ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Background Ebstein’s anomaly (EA) exhibits significant anatomical and clinical heterogeneity, warranting a systematic ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...
ABSTRACT: In order to solve the problem of chronic heart failure risk prediction in the elderly, a logistic regression modeling framework with Bayesian method was proposed, aiming to solve the problem ...
Background: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD). Methods: Patients with T2DM who underwent ...
Introduction: Ovarian Cancer (OC) is one of the leading causes of cancer deaths among women. Despite recent advances in the medical field, such as surgery, chemotherapy, and radiotherapy interventions ...
This project explores and evaluates multiple classification algorithms, including K-Nearest Neighbors (KNN), Logistic Regression, Support Vector Machines (SVM), and ensemble methods (Boosting and ...
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