Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by ...

When Arinze Nkemdirim Okere, PharmD, MBA, worked as the pharmacist for a hospital in Tallahassee, Florida, he noticed that ...

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial ...

Across the University of Pennsylvania Health System, scientists are now using AI to enhance their understanding of biological systems and modern medicine.

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...

Preventing high blood glucose (pre-diabetes) from turning into type 2 diabetes with lifestyle changes could more than halve ...

Abstract: Diabetes is a chronic condition affecting millions of people globally, requiring early and accurate prediction to mitigate associated health risks. This study employed a Kaggle dataset with ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Background: Despite the widespread use of immune checkpoint inhibitors (ICIs) in advanced clear cell renal cell carcinoma (ccRCC), therapeutic resistance persists. The prognostic and immunomodulatory ...

Background: Coronary artery disease (CAD) demonstrates a strong bidirectional association with diabetes mellitus, which not only elevates cardiovascular disease risk but also correlates with poorer ...

A comprehensive machine learning solution for predicting productivity in garment manufacturing facilities using historical production data. This project enables factory managers to optimize resource ...

Diabetes affects over 537 million adults globally, with early detection critical for effective treatment and management. This project develops a machine learning classification model to predict ...