ABSTRACT: Glioblastoma multiforme (GBM) remains one of the most aggressive brain malignancies, with a median survival of less than 15 months. This study advances glioblastoma multiforme (GBM) survival ...

Abstract: In scenarios with limited training data or where explainability is crucial, conventional neural network-based machine learning models often face challenges. In contrast, Bayesian ...

Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...

Build production-grade machine learning models with just 50-200 observations per business entity. SmallML combines transfer learning, hierarchical Bayesian inference, and conformal prediction to ...

ABSTRACT: Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the ...

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

Leptin, primarily secreted by adipose tissue, is a critical hormone involved in regulating energy balance and food intake by inducing satiety. Although several hormones influence satiety, leptin plays ...

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

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...

Appropriate vancomycin trough levels are crucial for ensuring therapeutic efficacy while minimizing toxicity. The aim of this study is to identify clinical factors that influence the steady-state ...

Abstract: Predicting transformer degradation is essential for ensuring the reliability and efficiency of power systems. This study explores Bayesian inference as a robust alternative to traditional ...