Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
CFO.com

Machine learning improves earnings forecast accuracy by 7%

A new research paper shows the approach performs significantly better than the random-walk forecasting method.
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

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

A clinical prediction model for schizophrenia based on machine learning algorithms

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...
Scientific Research Publishing

Johnson, A. and Lee, M. (2022) Predictive Modeling for Cardiovascular Risk Assessment Using Logistic Regression and Deep Learning. Journal of Biomedical Informatics, 130 ...

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...
Frontiers

Survival prediction modelling in patients with acute ST-segment elevation myocardial infarction with LASSO regression and explainable machine learning

Background: Acute ST-segment elevation myocardial infarction (STEMI) is a cardiovascular emergency that is associated with a high risk of death. In this study, we developed explainable machine ...
Visual Studio Magazine

Linear Regression Using JavaScript

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, ...
Visual Studio Magazine

Linear Regression Using JavaScript

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 ...
Scientific Research Publishing

Xie, Z., Jin, J., Liu, D.S., et al. (2024) Construction of a Predictive Model for the Death Risk of Patients with Septic Shock Based on Supervised Machine Learning Algorithms ...

ABSTRACT: Objective: To develop and validate a machine learning-based risk prediction model for postoperative nausea and vomiting (PONV) following gynecological day hysteroscopy, providing ...
IEEE

House Price Prediction Using Regression in Machine Learning

Abstract: The house pricing projection is crucial to the financial services industry and real estate sector. People are researching market techniques and attempting to purchase a new property within ...