The Evolution of Forensic Medicine: Harnessing Artificial Intelligence for Timeless Integrity

Dear Colleagues,

This editorial board is glad to introduce a new Special Issue regarding the impact of artificial intelligence in both forensic and medico-legal fields.

The scientific community is currently addressing the topic of the growth of artificial intelligence in the medical field. AI is experiencing significant growth and is assuming a role of great relevance, even replacing medical behavior. There is virtually no area in forensic medicine and care delivery that is not already impacted by AI.

Indeed, the deployment of deep learning models should facilitate medical procedures, minimizing human intervention to the greatest extent possible.

The information derived from learning leads to two computational consequences: the ability to respond according to a mechanism of machine learning and a capacity to anticipate possible scenarios. Through the rendering produced by artificial intelligence, it is possible to reconstruct the dynamics of an incident and formulate increasingly realistic hypotheses. This practice must undergo scrutiny during legal proceedings.

In autopsy practice, artificial intelligence can be useful in evaluating the presence of artifacts in diagnostic investigations and comparing them with forensic and medicolegal data. The ability of artificial intelligence to make decisions autonomously is influencing medical practice, opening avenues of healthcare responsibility. In this sense, even the activity of clinical risk management is influenced, as well as the assessment of damage and subsequent compensation.

In this Special Issue, we aim to address the theme of how artificial intelligence is impacting forensic professionals. Furthermore, it is important to focus on the ways in which AI is utilized, its strengths and limitations, and how it influences the justice system. The aim is to cover some topics such as the following:

1. Forensic pathology;
2. Forensic biology;
3. Forensic genetics;
4. Forensic toxicology;
5. Post-mortem examination;
6. Virtopsy;
7. Deep learning;
8. Machine learning;
9. Medical liability;
10. Health compensation;
11. Clinical risk management.

Dr. Aniello Maiese
Dr. Raffaele La Russa
Guest Editors

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• artificial intelligence
• deep learning
• autopsy
• forensic
• virtopsy