This overview examines the integration of machine learning (ML) approaches into diabetes prediction and diagnosis, highlighting the evolution from classical statistical methods to advanced data ...

Managing diabetes is a daily challenge faced by nearly 40 million Americans. It involves tracking food intake, timing ...

For patients with type 2 diabetes or the APOL1-HR genotype, a machine learning test integrating biomarkers and electronic health record data demonstrated improved prediction of kidney failure ...

Staying active is one of the most important things you can do for your health. Regular exercise helps you live longer, lowers ...

Machine learning plays a crucial role in enhancing climate services. AI algorithms improve regional simulations and forecasts, offering better support for water resource planning and management.

The performance of different machine learning models in detecting hepatitis among people with diabetes.

The same type of machine learning methods used to pilot self-driving cars and beat top chess players could help type-1 diabetes sufferers keep their blood glucose levels in a safe range.

MOF-MoS2 Nanosheets Doped PEDOT:PSS for Organic Electrochemical Transistors in Enhanced Glucose Sensing and Machine Learning-based Concentration Prediction [J]. Materials Futures.

New research presented during the 2024 San Antonio Breast Cancer Symposium (SABCS) reveals a new machine learning model that could change the way metastatic breast cancer is treated in the future. By ...