The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
BMJ Open

Psychological burden and its association with preferred form of psychological assistance of healthcare workers during the COVID-19 pandemic in China: a cross-sectional study

Objective This study focused on the preferences for psychological assistance and associated factors among Chinese healthcare workers (HCWs) during the COVID-19 pandemic. Design Cross-sectional ...
IEEE

A survey of applications of simple and multiple linear regression in solar power generation

Abstract: The aim of this paper is to present the results of literature survey on the application of simple and multiple linear regression (to be called regression henceforth in this paper) technique ...
Scientific Research Publishing

Chill Hours Record: A Sensitive Method for Climate Change Indication ()

Gophen, M. and Peres, M. (2026) Chill Hours Record: A Sensitive Method for Climate Change Indication. Open Journal of Modern ...
IEEE

Research and Prediction Based on Multiple Linear Regression and Machine Learning

Abstract: In this paper, a multivariate linear regression model is built for prediction based on SBPE Dataset by drawing heat maps to select relevant features. All 80% of the data is used as a ...
Scientific Research Publishing

Predictors of Opioid Use among Active-Duty Soldiers Following Postoperative Prescription ()

Predictors of Opioid Use among Active-Duty Soldiers Following Postoperative Prescription. Pain Studies and Treatment, 14, ...

Financial word of the day: Heteroscedasticity — meaning, usage, and why it matters more than ever

Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...
Open Heart

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

AI model forecasts coral heat stress on Florida reefs up to six weeks ahead

Scientists have created an AI model that forecasts moderate heat stress—a major precursor to coral bleaching—at sites along ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...