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Artificial intelligence in forensic science: Evaluation of ChatGPT for post-mortem interval estimation and Henssge nomogram use.

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Τίτλος: Artificial intelligence in forensic science: Evaluation of ChatGPT for post-mortem interval estimation and Henssge nomogram use.
Συγγραφείς: Giovannini E; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy., Santelli S; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy., Lenzi J; Department of Hygiene and Public Health, University of Bologna, Italy., Pelletti G; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy., Berti L; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy., Giorgetti A; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy., Pirani F; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy., Pelotti S; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy., Fais P; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.; Legal Medicine and Risk Management Unit, Azienda Unita Sanitaria Locale (USL) di Bologna, Italy.
Πηγή: Advances in clinical and experimental medicine : official organ Wroclaw Medical University [Adv Clin Exp Med] 2026 Aug; Vol. 35 (8), pp. 1437-1444.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Wroclaw Medical University Country of Publication: Poland NLM ID: 101138582 Publication Model: Print Cited Medium: Print ISSN: 1899-5276 (Print) Linking ISSN: 18995276 NLM ISO Abbreviation: Adv Clin Exp Med Subsets: MEDLINE
Imprint Name(s): Original Publication: Wroclaw, Poland : Wroclaw Medical University
Ιατρικοί όροι (MeSH): Forensic Sciences*/methods , Postmortem Changes* , Artificial Intelligence* , Nomograms*, Humans ; Generative Artificial Intelligence ; Large Language Models ; Autopsy ; Time Factors
Περίληψη: Background: In recent years, advancements in artificial intelligence (AI) have led to the creation of numerous large language models, including Chat Generative Pre-trained Transformer (ChatGPT), a natural language processing model developed by OpenAI. There has been increasing interest in exploring the potential of this tool, as evidenced by several studies in the healthcare domain that have investigated the performance of ChatGPT in responding to specific questions on relevant topics. However, its application in forensic contexts remains largely unexplored.
Objectives: This study aims to evaluate the performance of ChatGPT in estimating the post-mortem interval (PMI) by considering thanatochronological changes as well as through the application of the Henssge nomogram.
Material and Methods: Fifteen questions concerning PMI estimation were presented to ChatGPT. These questions were categorized into 3 domains, each addressing different aspects: 1) theoretical notions, 2) practical application of theoretical notions, and 3) utilization of the Henssge nomogram. The evaluation of responses included 3 sub-criteria: focus, accuracy, and completeness.
Results: The results showed a high level of accuracy and completeness in addressing theoretical issues. However, the AI failed when responding to practical case scenarios and when calculating PMI using the Henssge nomogram.
Conclusions: Although AI may be attractive for application to forensic science questions, uncertain source documents and incomplete access to the scientific literature may affect accuracy. The study concluded that AI should be investigated for use in forensic science; however, it is currently not suitable for practical PMI estimation.
Contributed Indexing: Keywords: ChatGPT; artificial intelligence; performance evaluation; post-mortem interval; post-mortem interval estimation
Entry Date(s): Date Created: 20260802 Date Completed: 20260903 Latest Revision: 20260903
Update Code: 20260903
DOI: 10.17219/acem/211777
PMID: 42543033
Βάση Δεδομένων: MEDLINE
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  Data: Artificial intelligence in forensic science: Evaluation of ChatGPT for post-mortem interval estimation and Henssge nomogram use.
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  Data: <searchLink fieldCode="AU" term="%22Giovannini+E%22">Giovannini E</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Santelli+S%22">Santelli S</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Lenzi+J%22">Lenzi J</searchLink>; Department of Hygiene and Public Health, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Pelletti+G%22">Pelletti G</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Berti+L%22">Berti L</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Giorgetti+A%22">Giorgetti A</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Pirani+F%22">Pirani F</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Pelotti+S%22">Pelotti S</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.<br /><searchLink fieldCode="AU" term="%22Fais+P%22">Fais P</searchLink>; Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Italy.; Legal Medicine and Risk Management Unit, Azienda Unita Sanitaria Locale (USL) di Bologna, Italy.
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  Data: <searchLink fieldCode="JN" term="%22101138582%22">Advances in clinical and experimental medicine : official organ Wroclaw Medical University</searchLink> [Adv Clin Exp Med] 2026 Aug; Vol. 35 (8), pp. 1437-1444.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wroclaw+Medical+University%22">Wroclaw Medical University </searchLink><i>Country of Publication: </i>Poland <i>NLM ID: </i>101138582 <i>Publication Model: </i>Print <i>Cited Medium: </i>Print <i>ISSN: </i>1899-5276 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2218995276%22">18995276 </searchLink><i>NLM ISO Abbreviation: </i>Adv Clin Exp Med <i>Subsets: </i>MEDLINE
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  Data: <i>Original Publication</i>: Wroclaw, Poland : Wroclaw Medical University
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  Data: <searchLink fieldCode="MM" term="%22Forensic+Sciences%22">Forensic Sciences*</searchLink>/<searchLink fieldCode="MM" term="%22Forensic+Sciences+methods%22">methods</searchLink> <br /><searchLink fieldCode="MM" term="%22Postmortem+Changes%22">Postmortem Changes*</searchLink> <br /><searchLink fieldCode="MM" term="%22Artificial+Intelligence%22">Artificial Intelligence*</searchLink> <br /><searchLink fieldCode="MM" term="%22Nomograms%22">Nomograms*</searchLink><br /><searchLink fieldCode="MH" term="%22Humans%22">Humans</searchLink> ; <searchLink fieldCode="MH" term="%22Generative+Artificial+Intelligence%22">Generative Artificial Intelligence</searchLink> ; <searchLink fieldCode="MH" term="%22Large+Language+Models%22">Large Language Models</searchLink> ; <searchLink fieldCode="MH" term="%22Autopsy%22">Autopsy</searchLink> ; <searchLink fieldCode="MH" term="%22Time+Factors%22">Time Factors</searchLink>
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  Data: Background: In recent years, advancements in artificial intelligence (AI) have led to the creation of numerous large language models, including Chat Generative Pre-trained Transformer (ChatGPT), a natural language processing model developed by OpenAI. There has been increasing interest in exploring the potential of this tool, as evidenced by several studies in the healthcare domain that have investigated the performance of ChatGPT in responding to specific questions on relevant topics. However, its application in forensic contexts remains largely unexplored.<br />Objectives: This study aims to evaluate the performance of ChatGPT in estimating the post-mortem interval (PMI) by considering thanatochronological changes as well as through the application of the Henssge nomogram.<br />Material and Methods: Fifteen questions concerning PMI estimation were presented to ChatGPT. These questions were categorized into 3 domains, each addressing different aspects: 1) theoretical notions, 2) practical application of theoretical notions, and 3) utilization of the Henssge nomogram. The evaluation of responses included 3 sub-criteria: focus, accuracy, and completeness.<br />Results: The results showed a high level of accuracy and completeness in addressing theoretical issues. However, the AI failed when responding to practical case scenarios and when calculating PMI using the Henssge nomogram.<br />Conclusions: Although AI may be attractive for application to forensic science questions, uncertain source documents and incomplete access to the scientific literature may affect accuracy. The study concluded that AI should be investigated for use in forensic science; however, it is currently not suitable for practical PMI estimation.
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  Data: <i>Keywords: </i>ChatGPT; artificial intelligence; performance evaluation; post-mortem interval; post-mortem interval estimation
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      – SubjectFull: Large Language Models
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      – SubjectFull: Nomograms
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              Text: 2026 Aug
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