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Ying-Lin Hsu

As seen in: Nature, Wiley Online Library
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Articles

Revenue-sensitive evaluation of AI-assisted ICD-10-CM coding and human-AI collaboration under dual DRG payment systems

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By Ying-Lin Hsu, Yi-Hsin Chen, Ming-I. Chen
| Nature Verified
Abstract Automated ICD-10-CM coding is critical for hospital reimbursement under Diagnosis-Related Group (DRG) payment systems, yet standard metrics weight all errors equally. This study evaluated 11 models on MIMIC-IV under heterogeneous conditions (the full 7942-code space, top-50 self-trained baselines, and 200-admission zero-shot LLM samples) and proposed two revenue-sensitive metrics: the Revenue Sensitivity Index (RSI) and Coding Reimbursement Score (CRS).
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Bayesian Forecasting of Value‐at‐Risk and Expected Shortfall in Cryptocurrency Markets: A Nonlinear Semi‐Parametric Framework

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By Po-Hui Chen, Ying-Lin Hsu
| Wiley Online Library Verified
Conflicts of Interest The authors declare no conflicts of interest. Supporting Information Filename Description asmb2926-sup-0001-Supplementary.pdfPDF document, 4.9 MB Data S1. Supporting Information. References 1, , , and , “Blocks and Chains: Introduction to Bitcoin, Cryptocurrencies, and Their Consensus Mechanisms,” Synthesis Lectures on Information Security, Privacy, & Trust 9, no. 1 (2017): 1–123.
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