Background Cardiogenic shock (CS) complicating acute myocardial infarction (AMI) carries high mortality. Early ...

Background Aortic stenosis (AS) frequently coexists with heart failure (HF), but its prevalence, prognostic impact and management across the full HF spectrum remain incompletely characterised. Methods ...

heart-disease-logistic-regression/ ├── data/ # dataset (heart_disease_uci.csv) ├── src/ # source code │ ├── heart_disease_logistic_regression.py │ └── plot_results.py ├── figures/ # generated plots ...

Objective: This study aims to develop and internally validate a multivariable logistic regression model and a simplified scoring system, based on standardized ultrasonographic features, for the ...

Background: Aspiration pneumonia is a serious complication after cardiac surgery, particularly among older patients. Preoperative oral frailty—decline in oral function including poor hygiene and ...

Abstract: Effective sedation and pain management in Intensive Care Unit (ICU) patients are essential for enhancing patient outcomes and providing comfort. This research used logistic regression (LR) ...

The company has since taken down the image of the accused killer. Fast fashion giant Shein is conducting an investigation of its internal processes after using the likeness of Luigi Mangione to model ...

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...

1 Department of Hepatology, Panzhihua Hospital of Integrated Chinese and Western Medicine, Panzhihua, China 2 Department of Intensive Care Medicine, Panzhihua Hospital of Integrated Chinese and ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee's salary based on age, height, years of experience, and so on ...