Majid Afshar

You are already at the latest version Feature selection remains a fundamental challenge in modern machine learning, particularly in ultra-high-dimensional domains such as genomics, text mining, cybersecurity, and bioinformatics, where the number of features can exceed the number of samples by several orders of magnitude.

[Submitted on 9 Jul 2025 ( v1 ), last revised 5 Sep 2025 (this version, v2)] Title:Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification View a PDF of the paper titled Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification, by Maya Kruse and 5 other authors View PDF HTML (experimental) Abstract:Large language models (LLMs) often behave inconsistently across inputs, indicating uncertainty and motivating the need...

Abstract Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and repeated hospital admissions. Routine screening for patients at risk for an OUD to prevent complications is not standard practice in many hospitals, leading to missed opportunities for intervention. The adoption of electronic health records (EHRs) and advancements in artificial intelligence (AI) offer a scalable approach to systematically identify at-risk patients for evidence-based care.