Artificial intelligence and future perspectives in Forensic Medicine: a systematic review.

Abstract

Objective: Artificial intelligence (AI) is the ability of a computer machine to display human capabilities such as reasoning, learning, planning, and creativity. Such processing technology receives the data (already prepared or collected), processes them, using models and algorithms, and answers questions about forecasting and decision-making. AI systems are also able to adapt their behavior by analyzing the effects of previous actions and working then autonomously. Artificial intelligence is already present in our lives, even if it often goes unnoticed (shopping networked, home automation, vehicles). Even in the medical field, artificial intelligence can be used to analyze large amounts of medical data and discover matches and patterns to improve diagnosis and prevention. In forensic medicine, the applications of AI are numerous and are becoming more and more valuable.

Method: A systematic review was conducted, selecting the articles in one of the most widely used electronic databases (PubMed). The research was conducted using the keywords "AI forensic" and "machine learning forensic". The research process included about 2000 Articles published from 1990 to the present.

Results: We have focused on the most common fields of use and have been then 6 macro-topics were identified and analyzed. Specifically, articles were analyzed concerning the application of AI in forensic pathology (main area), toxicology, radiology, Personal identification, forensic anthropology, and forensic psychiatry.

Conclusion: The aim of the study is to evaluate the current applications of AI in forensic medicine for each field of use, trying to grasp future and more usable applications and underline their limitations.