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 ...
News-Medical.Net

AI trained on sleep data predicts future disease and mortality years in advance

The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

AI river forecasts may be accurate, but based on flawed logic

Artificial intelligence is changing how we predict river flow—but a new study led by researchers at the University of British ...
Frontiers

Prediction of total iodine dose of I-131 therapy for Graves’ hyperthyroidism achieved remission status: a random forest regressor model approach to assess treatment efficacy

Department of Nuclear Medicine, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi Zhuang Autonomous Region, China Objective: Graves’ hyperthyroidism (GH) presents significant ...
IEEE

Comparative Study of Machine Learning Models for Diabetes Prediction

Abstract: Diabetes is one of the most widespread and critical health issues globally, attributed to factors such as obesity, sedentary lifestyles, and elevated blood sugar levels. These factors ...
Frontiers

Predicting cognitive impairment in Parkinson’s disease: a machine learning approach based on clinical and neuropsychological data

Background: Cognitive impairment is a common and disabling non-motor symptom of Parkinson’s disease, markedly diminishing quality of life and elevating caregiver burden. Although considerable research ...