Machine learning accelerates analysis of fusion materials

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...
Frontiers

Machine learning–guided feature selection and predictive model construction for attention-deficit/hyperactivity disorder

A total of 8,598 children were enrolled and classified into three groups: ADHD (n=3,678), subthreshold ADHD (s-ADHD) (n=1,495), and healthy controls (HC) (n=3,425). Data collection covered 40 ...
IEEE

An ECG Data Feature Selection Comparison: Machine Learning and Expert Doctors

Abstract: The ECG signals analysis is a frequently used approach for classification of cardiac patients. Traditionally, this analysis is made by expert doctors. However, recently, it is increasingly ...
ahajournals.org

Abstract 4368538: Fusion Machine Learning Architectures for Improving ECG classification of acute coronary events

Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...
Scientific Research Publishing

Comparative Research in Sentiment Analysis Using Machine Learning Technique ()

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...
EDN

DIY EKG Using Arduino and Javascript

An electrocardiogram or EKG is a testing equipment used to measure the electrical activity of the heart. Using only an Arduino Shield and a set of electrodes, one can create his own EKG, generate a ...