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 ...
Nature

Chronic Kidney Disease Prediction Using Machine Learning Techniques

Chronic kidney disease (CKD) constitutes a major global health challenge, affecting millions and often remaining undiagnosed until advanced stages. Recent advances in machine learning have ...
News-Medical.Net

Using Artificial Intelligence to Predict Chronic Disease Through Diet and Multi-Omics Data

Discover how AI is transforming nutritional science by turning complex diet and omics data into predictive tools that reshape chronic disease prevention and personalized care.

Valinor and Renew Launch Partnership to Generate Largest Clinical Multi-Omics Dataset for Neurological Disease Model Development

The partnership integrates high-resolution multi-omics data generation with predictive multimodal machine learning to support biopharma decision-making in neurology.
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 ...
WLRN

'95% accuracy': FIU researchers use artificial intelligence to detect heart disease early

FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction. The future of heart ...

AI model developed by OUTR, Saudi Univ researchers predicts liver disease with 95.49% accuracy

Researchers from Odisha and Saudi Arabia have developed a hybrid AI model achieving 95.49% accuracy in predicting liver disease. This innovative tool, combining deep learning and boosting, promises ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
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 ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...
Technology Networks

Machine Learning Applications in Proteomics

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.