Objective:

To analyze the potential benefits and inherent risks associated with the application of artificial intelligence in forensic medicine.

Approach:

Key Findings:

• AI can analyze gunshot wounds, determine shooting distance, and distinguish between entry and exit wounds.
• Post-mortem CT is useful for determining the cause of death.
• AI can estimate dental age with high precision in forensic odontology.
• AI supports mental illness assessment in forensic psychiatry.
• Chen et al. identified potential PMI biomarkers through metabolomics analysis.
• Delogu et al.'s AI model effectively recognizes gunshot wound characteristics.
• Wang et al.'s BIPON system improves diagnostic evidence interpretation.

Interpretation:

AI should be viewed as a decision-support tool, with final decisions remaining in human hands due to ethical and legal implications.

Limitations:

• AI models require a larger dataset for effective training and judicial application.
• Integration of AI into forensic practice necessitates collaboration among various experts.

Conclusion:

AI technologies present opportunities for methodological advancements in forensic medicine, enhancing the analytical capabilities of forensic experts.

Attribution Notice

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.