AI-enabled ECG biological age (ECG-BA) improves disease risk classification beyond chronological age, enhancing early ...

To develop a machine learning (ML) algorithm to predict survival probabilities for patients with epithelial ovarian cancer (EOC).Data were obtained from the SEER database for women diagnosed with EOC ...

While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for clinical adoption. Healthcare professionals require AI models to not only be ...

After combing through 4,000 existing medications, an artificial intelligence tool helped uncover one that saved the life of a patient with idiopathic multicentric Castleman's disease (iMCD).

Though highly effective, medications for the prevention of chronic kidney disease progression are under-utilized, emphasizing the need for better use of prognostic tools.

Heart health is becoming an increasingly ... tests might only detect issues after the disease has inflicted harm. "The markers we use to diagnose a condition are late markers or maybe even the ...

Eko Health has been advancing the use of artificial intelligence to help providers detect the early signs of disease, ...

People's bodies can be old or young for their chronological age, depending, in part, on the amount and types of stressors ...

Electrocardiogram tests – which measure the heart's electrical activity – could someday be paired with an artificial intelligence model to detect premature aging and cognitive decline, new research ...

Many commercial biological age tests collect genetic information through saliva samples or oral swabs. For accurate measurements, however, blood samples are typically necessary according to a new ...