BMJ Open

Using virtual twin-based AI models to detect atrial fibrillation and improve stroke outcomes [TAILOR]: a multicentre prospective cohort study

Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...
IEEE

Gender Classification Based on Machine Learning Models

Abstract: Automatic gender categorization has become an increasingly significant area in computer vision, with several applications. Gender equality is nowadays a keyword for today's scenario. This ...
IEEE

Severity Classification of Freezing of Gait Using Machine-Learning Algorithms: A Hidden State Model Approach

Abstract: E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. A chronic disease requires active monitoring and its severity increases ...
THE WEEK

To the point: the gender divide over exclamation marks

Shocking! Women use exclamation marks three times more often than men, according to a new study. Punctuation is a “fraught and contentious business”, said Melanie McDonagh in London’s The Standard.
Frontiers

Construction and clinical visualization application of a predictive model for mortality risk in sepsis patients based on an improved machine learning model

Objective: To explore the construction and clinical visualization application of a mortality risk prediction model for sepsis patients based on an improved machine learning model. Methods: This ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
Science Daily

Researchers use machine learning to predict exercise adherence

Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...