> ## Content Index > Fetch the complete content index at: https://www.coios.me/llms.txt > Use this file to discover other available public pages before exploring further. # Fine-tuned LLM beat ICD codes for in-hospital cardiac arrest on a curated corpus - URL: https://www.coios.me/fine-tuned-llm-beat-icd-codes-for-in-hospital-cardiac/ - Published: 2026-09-29T12:50:50.000Z - Updated: 2026-09-29T21:01:50.000Z - Description: Large language models reading clinical notes identified in-hospital cardiac arrest with precision 0.88 and recall 1.00 on a curated corpus against 0.68 and 0.91 for ICD codes, though a prompting configuration reached precision 0.79 in an unselected cohort of 45,525 encounters. - Author: Daniel Ryan - Tags: Weighing data and models, AI in medicine, Heart and stroke, #preprint, #new, #item, #source-2026-09 Researchers built LLM systems combining guideline-enriched prompting, supervised fine-tuning and a self-correction step to identify in-hospital cardiac arrest events and their locations from electronic health record notes, benchmarked against physician-adjudicated chart review. On a curated corpus the fine-tuned model reached precision 0.88, recall 1.00 and F1 0.94, against 0.68, 0.91 and 0.78 for an ICD-code algorithm. In an unselected cohort of 45,525 encounters the fine-tuned model underperformed, while a prompting-plus-self-correction configuration achieved precision 0.79. *Why it is interesting: The gap between performance on a curated corpus and in an unselected cohort of 45,525 encounters, where the fine-tuned model underperformed.* Source [medRxiv, 27 September 2026](https://doi.org/10.64898/2026.09.24.26363973?ref=coios.me) DOI 10.64898/2026.09.24.26363973 Type Preprint Design Retrospective LLM case-ascertainment study against physician-adjudicated chart review; curated evaluation corpus plus 45,525-encounter unselected validation cohort Verdict New finding Driver [AI in medicine](https://www.coios.me/d-ai-medicine/) Driver [Heart and stroke](https://www.coios.me/d-cardiovascular/)