Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...

Understanding the derivative of the cost function is key to mastering logistic regression. Learn how gradient descent updates weights efficiently in machine learning. #MachineLearning ...

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 ...

Doing logistic regression with a binary outcome using the Generalized Linear Model analysis in Regression module should work. This works fine in Regression > Logistic Regression.

Across the literature, multivariable models for predicting giant cell arteritis diagnoses showed various methodological weaknesses. Multivariable models can aid in the diagnosis of giant cell ...

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 ...

Objective: To develop and validate a clinical prediction model for moderate-to-severe tinnitus (THI ≥ 38) in patients with hearing loss and to identify the key psychological and clinical factors ...

Department of Hepatobiliary Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China Objective: Compare the performance of the Multivariable logistic ...

Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...