Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...
Oak Ridge National Lab

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial ...
IEEE

Improving Accuracy of Diabetes Prediction Using Machine Learning Techniques and Clinical Data

Abstract: Diabetes is a chronic condition affecting millions of people globally, requiring early and accurate prediction to mitigate associated health risks. This study employed a Kaggle dataset with ...
Frontiers

Development and comparison of machine learning models for predicting moderate-to-severe tinnitus in patients with hearing loss

Objective: Analyze the psychological and clinical factors of clinically significant tinnitus (THI score ≥38) in patients with hearing loss, construct predictive models based on four machine learning ...
Frontiers

Classification of angioedema types using decision tree modeling

Introduction: All angioedema (AE) presents with transient, localized swelling; however, the underlying causes, prognosis, and treatments vary significantly. Consequently, identifying a specific AE ...
IEEE

Obesity Health Risk Prediction using Random Forest and SVM Algorithms

Abstract: Obesity-related health dangers have become a serious global issue that requires adequately pinpointing and quickly preventing health problems. One of the research studies in the article ...