Age, gender, and lifestyle are key factors in predicting risks for illnesses like cancer and heart disease, but adding race ...

Inclusion of measures of depression and anxiety to the American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) prediction model has little additional impact on risk ...

Subhro Mallik highlights the transformative role of AI and predictive analytics in chronic disease management, offering early ...

LG AI Research will collaborate with a Seoul National University (SNU) professor team to develop an artificial intelligence ...

While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for ...

The AI-driven predictive model is expected to interpret combined data from CT scans, clinical risk factors, and demographic ...

In simulated trial, FDI achieved mean absolute errors of 1.57 and 0.70 years for predicting MCI, AD onset, respectively.

A multi-task learning framework, DEMENTIA, has been developed by Prof. Li Hai and his team at the Hefei Institutes of ...

A collaboration between the Ragon Institute and the Jameel Clinic at MIT has achieved a significant milestone in leveraging ...

Although ctDNA positivity generally meant worse disease-free survival in stage 3 resected colon cancer, patients with ctDNA ...

Epigenetic clocks that quantify rates of aging from DNA methylation patterns across the genome have emerged as a potential biomarker for risk of age-related diseases, like Alzheimer’s disease (AD), ...