Risk adjustment is often necessary for outcome quality indicators (QIs) to provide fair and accurate feedback to healthcare professionals. However, traditional risk adjustment models are generally ...

Artificial intelligence (AI) increasingly powers safety-critical systems that demand robust, energy-efficient computation, often under conditions of data scarcity and uncertainty. Traditional AI ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...