Abstract

The upcoming Industrial transformation will be distinguished by the dominion of Artificial    Intelligence (AI). The domain of Medical Jurisprudenceispivotal to criminal inquiries. AI  has the capability to prevail over countless of the constraints linked with the conventional  procedures of regulating post-mortem examinations & framing inferences. AI will be pivotal   in framing various inferences of medico-legal significance in Medical juridical approaches such  as toxicological examination, collection of various specimens of medico-legal significance from cavities, recognition of pathologies in various organs, recognition of various stains, recognition  of a weapon of offence, post-mortem interval calculations & so on. AI can also be incorporated  into presently used investigation & examination approaches to speed up & boost the precision  of the procedure as a whole. AI will play a pivotal role in Medical Jurisprudence in future.

• 1.   Kumar Y, Koul A, Singla R, Ijaz MF: Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda. J Ambient Intell Humaniz Comput. 2022, 13:1-28.
• 2.   Meetali S, Sachan D, Parthasarathi R: Artificial intelligence in clinical toxicology. Artificial Intelligence inMedicine. Niklas Lidströmer, Hutan Ashrafian (ed): Springer, Cham; 2021. 1-15.
• 3.   Yadav M, Tiwari A: Forensic toxicology and its relevance with criminal justice delivery system in India. Forensic Res CriminolInt J. 2017, 4:122-8.
• 4.   Aggrawal A: Textbook of forensic medicine and toxicology. Anil Aggrawal (ed): Avichal Publication Company, New Delhi; 2014.
• 5.   Thurzo A, Kosnáčová HS, Kurilová V, et al.: Use of advanced artificial intelligence in forensic medicine, forensic anthropology and clinical anatomy. Healthcare (Basel). 2021, 9:1545.
• 6.   Matsuda S, Yoshimura H: Personal identification with artificial intelligence under COVID-19 crisis: a scoping review. Syst Rev. 2022, 11:7.
• 7.   Saini M, Kapoor AK: Biometrics in forensic identification: applications and challenges. J Forensic Med.2016, 1:108.
• 8.   Ramprabhu K, Fatangare S: Survey on prediction of post mortem interval using artificial intelligence inforensic examination. IRJET. 2020, 7:5760-3.
• 9.   Hachem M, Sharma BK: Artificial intelligence in prediction of post-mortem interval (PMI) through blood biomarkers in forensic examination-a concept. Amity International Conference on Artificial Intelligence (AICAI). 2019, 255-258.
• 10.   Helma C, Gottmann E, Kramer S: Knowledge discovery and data mining in toxicology. Stat Methods Med Res. 2000, 9:329-58.
• 11.   Agrebi S, Larbi A: Use of artificial intelligence in infectious diseases. Artificial Intelligence in PrecisionHealth: From concept to applications. Debmalya Barh (ed): Academic Press, London; 2020. 415-38.
• 12.   Akçan R, Taştekin B, Yildirim MŞ, Aydogan HC, Sağlam N: Omics era in forensic medicine: towards a newage. Turk J Med Sci. 2020, 50:1480-90. 10.3906/ sag-1912-197.
• 13.   Gaballah MH, Fukuta M, Maeno Y, et al.: Simultaneous time course analysis of multiple markers based onDNA microarray in incised wound in skeletal muscle for wound aging. Forensic Sci Int. 2016, 266:357-68.

Data Sharing Statement

Funding