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. 2024 May 31:2024:509-514.
eCollection 2024.

Large Language Models for Efficient Medical Information Extraction

Navya Bhagat  1 , Olivia Mackey  1 , Adam Wilcox  1
Affiliations

Large Language Models for Efficient Medical Information Extraction

Navya Bhagat et al. AMIA Jt Summits Transl Sci Proc. .

Abstract

Extracting valuable insights from unstructured clinical narrative reports is a challenging yet crucial task in the healthcare domain as it allows healthcare workers to treat patients more efficiently and improves the overall standard of care. We employ ChatGPT, a Large language model (LLM), and compare its performance to manual reviewers. The review focuses on four key conditions: family history of heart disease, depression, heavy smoking, and cancer. The evaluation of a diverse sample of History and Physical (H&P) Notes, demonstrates ChatGPT's remarkable capabilities. Notably, it exhibits exemplary results in sensitivity for depression and heavy smokers and specificity for cancer. We identify areas for improvement as well, particularly in capturing nuanced semantic information related to family history of heart disease and cancer. With further investigation, ChatGPT holds substantial potential for advancements in medical information extraction.

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Figures

Figure 1:
Figure 1:
Schematic of the manual review, automated review, and input of the H&P notes
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References

    1. Adamidi ES, Mitsis K, Nikita KS. Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review. Comput Struct Biotechnol J. 2021;19:2833–2850. doi: 10.1016/j.csbj.2021.05.010. Epub 2021 May 7. PMID: 34025952; PMCID: PMC8123783. - PMC - PubMed
    1. Ford E, Carroll JA, Smith HE, Scott D, Cassell JA. Extracting information from the text of electronic medical records to improve case detection: a systematic review. J Am Med Inform Assoc. 2016 Sep;23(5):1007–15. doi: 10.1093/jamia/ocv180. Epub 2016 Feb 5. PMID: 26911811; PMCID: PMC4997034. - PMC - PubMed
    1. Hirschberg J, Manning CD. Advances in natural language processing. Science. 2015 Jul 17;349(6245):261–6. doi: 10.1126/science.aaa8685. PMID: 26185244. - PubMed
    1. Hripcsak G, Friedman C, Alderson PO, DuMouchel W, Johnson SB, Clayton PD. Unlocking clinical data from narrative reports: a study of natural language processing. Ann Intern Med. 1995 May 1;122(9):681–8. doi: 10.7326/0003-4819-122-9-199505010-00007. PMID: 7702231. - PubMed
    1. Katz Daniel Martin, Bommarito Michael James, Gao Shang, Arredondo Pablo. GPT-4 Passes the Bar Exam. 2023. - PMC - PubMed

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