The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

Background and Goal: This study examined whether machine learning could predict the risk and contributing factors of no-shows and late cancellations in primary care practices. Study Approach: ...

University of Idaho receives over $6M in DoD grants to advance machine learning research for PTSD diagnosis and military ...

Overview Machine learning offers efficiency at scale, but trust depends on understanding how decisions are madeAs machine ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...