Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
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 ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Frontiers

Generalised machine learning models outperform personalised models for cognitive load classification in real-life settings

Introduction: By issuing work-break reminders, for example, personal assistants for cognitive load could be beneficial in maintaining health and life satisfaction in society. Wearable sensors ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
IEEE

Machine Learning-Based Classification of Suspension Droplet-Solid Wall Impacts for Control of Droplet Fragmentation

Abstract: This study explores the collision of suspension droplets against solid dry surfaces (substrates). It applies and compares multiple machine learning (ML) models for the classification of ...
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
GitHub

Consumer Complaints Text Classification Using Machine Learning

This project aims to build a multi-class text classification model for consumer complaint narratives.It categorizes complaints into four classes: Credit Reporting, Debt Collection, Consumer Loan, and ...
Hosted on MSN

Logistic Regression Machine Learning Example ¦ Simply Explained

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...