IEEE

Heart Disease Prediction System using Ensemble Machine Learning Technique

Abstract: The traditional approach to prediction of heart disease using a limited set of essential physical signs from repetitive inspections is inadequate. Also, manual inspection and analysis of ...
Opinion
TheCableOpinion

How AI and predictive modelling can transform public services in Nigeria

Nigeria faces enormous public service challenges from traffic congestion in high urbanised areas to insecurity, healthcare delays, and inconsistent public planning. But with the right use of ...
EurekAlert!

Data bias reduces reliability of AI models predicting antimicrobial resistance

Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance mechanisms can be identified based on a pathogen’s genetics. However, the ...
Frontiers

Heart disease prediction using hybrid TabNet architecture with stacked ensemble learning

1 Department of Computer Science, National University of Modern Languages (NUML), Islamabad, Pakistan 2 Department of AI and SW, Gachon University, Seongnam, Republic of Korea Cardiovascular diseases ...
Healio

Machine learning, remote monitoring identify low disease activity in rheumatoid arthritis

Please provide your email address to receive an email when new articles are posted on . Machine learning can use patient-reported outcomes to identify low disease activity in rheumatoid arthritis.
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 ...
IEEE

Unified Disease Prediction System Using Machine Learning Techniques

Abstract: This innovative research uses datasets from Kaggle to leverage Machine Learning (ML) techniques to develop a complete unified disease prediction system. With its comprehensive coverage of ...
News Medical

Using AI models to improve prediction of CKD's progression to end-stage renal disease

Chronic kidney disease (CKD) is a complex condition marked by a gradual decline in kidney function, which can ultimately progress to end-stage renal disease (ESRD). Globally, the prevalence of the CKD ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
Frontiers

Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley ...

Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a prevalent and progressive liver disorder closely linked to obesity and metabolic dysregulation. Traditional anthropometric ...
Scientific Research Publishing

Di Noia, A., Martino, A., Montanari, P. and Rizzi, A. (2019) Supervised Machine Learning Techniques and Genetic Optimization for Occupational Diseases Risk Prediction. Soft ...

ABSTRACT: This study explores the use of neural networks for occupational disease risk prediction based on worker and workplace characteristics. The goal is to develop a tool to assist occupational ...