Evidence map›Paper›PMID 41457196›Full record

ArticleInternational journal of legal medicine2026

ChatGPT's performance on a specialist forensic pathology examination: implications for forensic pathologists and non-specialists.

Hans H de Boer, Gregory Young, Heinrich Bouwer, Karen J Heath

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Article in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hans H de BoerDepartment of Forensic Medicine, Monash University, 65 Kavanagh Street, Southbank, VIC, 3006, Australia. hans.de.boer@vifm.org.ORCID http://orcid.org/0000-0001-8590-0945
Gregory YoungDepartment of Forensic Medicine, Monash University, 65 Kavanagh Street, Southbank, VIC, 3006, Australia.
Heinrich BouwerDepartment of Forensic Medicine, Monash University, 65 Kavanagh Street, Southbank, VIC, 3006, Australia.
Karen J HeathForensic Science South Australia, Divett Place, Adelaide, SA, 5000, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe use of artificially intelligent Language Models (LLMs) like ChatGPT is increasing rapidly in medicine, but their accuracy, reasoning quality, and contextual safety remains an issue. This is especially relevant for forensic pathology, where balanced reasoning, contextual sensitivity, and precise communication are essential. We performed an in-depth assessment of ChatGPT's capabilities and limitations for forensic pathology, which also improves our understanding of the risks and benefits of LLM use in medicine more broadly.

methodsChatGPT-4.5 Turbo's performance was tested using a multifaceted mock exam, consisting of core elements of the forensic pathology fellowship exam of the Royal College of Pathologists of Australasia (RCPA). The mock exam included essay-style questions, image-based tasks, and case reporting. ChatGPT's responses were blindly marked by experienced examiners according to standard RCPA criteria, assessing factual accuracy, reasoning structure, and communication quality.

resultsChatGPT performed well on most essay-style knowledge questions, achieving higher scores on topics with well-established knowledge. Performance was however poor for tasks requiring complex reasoning, image interpretation, or the context-dependent analysis of autopsy findings. Importantly, ChatGPT's output was always phrased fluently and persuasively, creating an impression of confidence that was independent of factual accuracy.

conclusionsChatGPT can reliably reproduce well-established forensic pathology knowledge. However, it lacks the capabilities needed for higher-level tasks and often generates unjustifiably confident and misleading output. Its use may be acceptable for low-risk administrative or educational purposes, provided output is carefully reviewed by qualified experts. Non-specialists should not rely on such tools for forensic pathology information. Continued evaluation is needed to ensure safe and responsible use.

Indexed as

Educational MeasurementForensic PathologyGenerative Artificial IntelligenceHumansPathologistsArtificial intelligenceChatGPTDiagnostic reasoningForensic medicineForensic pathologyLarge language modelReportingValidation

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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.