What type of study is this?

This is a Observational study (also classified as: In Vitro Study).

August 20, 2025DiagnosticsOpen Access

From Description to Diagnostics: Assessing AI’s Capabilities in Forensic Gunshot Wound Classification

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Authors

FSFrancesco SessaPegaso University EGElena GuardoUniversity of Catania MEMassimiliano EspositoUniversità degli Studi di Enna Kore

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Implication

This analysis demonstrates ChatGPT-4’s diagnostic capabilities for gunshot wounds, suggesting potential in forensic applications while highlighting limitations.

Key Points

ChatGPT-4 achieved 95% accuracy in identifying intact skin, enhancing its potential for forensic diagnostics.
Significant improvements were noted in entrance wound identification after machine learning training, though exit wounds remained problematic.
The study utilized three distinct datasets, facilitating a robust assessment of AI classification performance in forensic contexts.
Cautious integration of AI in forensic workflows is essential to mitigate risks like overconfident misclassifications and hallucinations.

Cite This Study

Sessa et al. (2025) studied this question.

synapsesocial.com/papers/68af4ce5ad7bf08b1ead698c https://doi.org/10.3390/diagnostics15162094

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Implication

This analysis demonstrates ChatGPT-4’s diagnostic capabilities for gunshot wounds, suggesting potential in forensic applications while highlighting limitations.

From Description to Diagnostics: Assessing AI’s Capabilities in Forensic Gunshot Wound Classification

Discussion

Member takes

Implication

Key Points

Cite This Study

From Description to Diagnostics: Assessing AI’s Capabilities in Forensic Gunshot Wound Classification

Discussion

Member takes

Implication

Key Points

Cite This Study

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