Clinical Risk Computation by Large Language Models Using Validated Risk Scores
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View abstract on PubMed
Summary
This summary is machine-generated.Large Language Models (LLMs) can reliably calculate clinical risk scores, enhancing healthcare workflows. GPT-4o-mini and Gemini 2.5 Flash showed high accuracy, though complex scores like Framingham remain challenging for AI.
Area Of Science
- Artificial Intelligence in Medicine
- Clinical Informatics
- Natural Language Processing
Background
- Large Language Models (LLMs) offer advanced natural language understanding for healthcare.
- Direct LLM risk prediction is unreliable due to bias and data complexity.
- Using LLMs to compute established clinical risk scores enhances validity and transparency.
Purpose Of The Study
- To evaluate the accuracy of public LLMs in calculating validated clinical risk scores.
- To compare the performance of GPT-4o-mini, DeepSeek v3, and Google Gemini 2.5 Flash.
- To assess LLM reliability for enhancing clinical workflows through interpretable score calculation.
Main Methods
- Generated 100 diverse patient profiles as natural language clinical notes.
- Utilized LLMs (GPT-4o-mini, DeepSeek v3, Gemini 2.5 Flash) to extract data and compute five clinical risk scores.
- Compared LLM-computed scores against reference scores using accuracy, precision, recall, F1, and Pearson correlation.
Main Results
- GPT-4o-mini and Gemini 2.5 Flash demonstrated near-perfect agreement with reference scores for most clinical risk assessments.
- DeepSeek v3 showed lower performance compared to GPT-4o-mini and Gemini 2.5 Flash.
- All evaluated LLMs encountered difficulties with the complex Framingham Risk Score calculation.
Conclusions
- LLMs can accurately compute established clinical risk scores, offering a trustworthy alternative to direct AI risk prediction.
- GPT-4o-mini and Gemini 2.5 Flash show promise for integrating into clinical workflows for risk score calculation.
- Further development is needed to address LLM challenges with highly complex risk assessment formulas.
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