ArticleNPJ digital medicine2024
DRG-LLaMA : tuning LLaMA model to predict diagnosis-related group for hospitalized patients.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 3 of them syntheses that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
58 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Performance and improvement strategies for adapting generative large language models for electronic health record applications: A systematic review.International journal of medical informatics · 2026Pooled it
- Accuracy of Large Language Models When Answering Clinical Research Questions: Systematic Review and Network Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review.JAMA · 2025Pooled it
- Tutorial: guidance on the use of large language models for medical research.Nature protocols · 2026Review
- Automated identification of keratinocyte cancers in pathology reports using large language models.PLOS digital health · 2026Article
- Memorization in large language models in medicine prevalence characteristics and implications.Nature communications · 2026Article
- A data and knowledge cross-level fusion-driven learning framework for detecting missing diagnosis.NPJ digital medicine · 2026Article
- Large Language Models for Clinical Narrative Processing: Methods, Applications, and Challenges.Methods and protocols · 2026Article
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- Domain specific multimodal large language model for automated endoscopy reporting with multicenter prospective validation.NPJ digital medicine · 2026Article
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- Large language models in emergency and critical care medicine: a comprehensive review of applications, challenges, and future directions.Burns & trauma · 2026Review
- Artificial intelligence-assisted medical coding and DRG management: current applications, challenges, and future perspectives.Frontiers in medicine · 2026Review
- MoMA: a mixture-of-multimodal-agents architecture for enhancing clinical prediction modelling.NPJ digital medicine · 2025Article
- A generative vision-language model for holistic pathological assessment using preoperative imaging in hepatocellular carcinoma.EBioMedicine · 2025Article
- A tree-structured multiobjective optimization framework for constructing diagnosis-related groups.NPJ digital medicine · 2025Article
- Large language model as clinical decision support system augments medication safety in 16 clinical specialties.Cell reports. Medicine · 2025Article
- From Single-Cancer to Pan-Cancer Prognosis: A Multimodal Deep Learning Framework for Survival Analysis with Robust Generalization Capability.The American journal of pathology · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
In the U.S. inpatient payment system, the Diagnosis-Related Group (DRG) is pivotal, but its assignment process is inefficient. The study introduces DRG-LLaMA, an advanced large language model (LLM) fine-tuned on clinical notes to enhance DRGs assignment. Utilizing LLaMA as the foundational model and optimizing it through Low-Rank Adaptation (LoRA) on 236,192 MIMIC-IV discharge summaries, our DRG-LLaMA -7B model exhibited a noteworthy macro-averaged F1 score of 0.327, a top-1 prediction accuracy of 52.0%, and a macro-averaged Area Under the Curve (AUC) of 0.986, with a maximum input token length of 512. This model surpassed the performance of prior leading models in DRG prediction, showing a relative improvement of 40.3% and 35.7% in macro-averaged F1 score compared to ClinicalBERT and CAML, respectively. Applied to base DRG and complication or comorbidity (CC)/major complication or comorbidity (MCC) prediction, DRG-LLaMA achieved a top-1 prediction accuracy of 67.8% and 67.5%, respectively. Additionally, our findings indicate that DRG-LLaMA 's performance correlates with increased model parameters and input context lengths.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.