The study advanced beyond a one-size-fits-all model by developing both a global XGBoost classifier and cancer-type-specific ...

An analysis of exhaled breath, using an electronic nose, demonstrates potential for accurately detecting lung cancer in ...

A novel diffusion model generates synthetic atrial fibrosis images to augment data for deep learning, improving prediction of ...

Electronic "nose" analysis of exhaled breath achieved 80-90% accuracy for detecting lung cancer in patients with suspicious clinical or radiologic findings, a large prospective study showed.

Patients with acute liver failure (ALF) or acute-on-chronic liver failure (ACLF) are at high risk of bleeding with ...

The following is a summary of “Visual coronary artery calcification score to predict significant coronary artery stenosis in ...

Researchers say findings provide compelling evidence underscoring the potential of electric-field molecular fingerprinting for minimally invasive disease detection.