News-Medical.Net

Machine learning model may provide an earning warning of preeclampsia in late gestation

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Machine learning can predict preeclampsia by week 34 of pregnancy

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
Frontiers

Eye-tracking biomarkers of clinical expertise in ECG interpretation: statistical and machine learning evidence

Second, this study integrates both supervised (RF, SVM, KNN) and unsupervised (K-means) machine learning approaches to classify expertise, providing complementary evidence on the discriminability and ...
Scientific Research Publishing

An Explainable Wavelet-Based Feature Decomposition and Machine Learning Framework for Land Cover Classification ()

1 Department of Geomatic Engineering, University of Mines and Technology, Tarkwa, Ghana. 2 Department of Geomatic and Civil Engineering, University of Mines and Technology, Essikado, Ghana. Accurate ...
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

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 supported ...
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 ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...