PERCEPTION ABOUT USE OF ARTIFICIAL INTELLIGENCE APPLICATIONS IN FORENSIC MEDICINE AMONG TEACHING FACULTIES AND POSTGRADUATE STUDENTS OF FORENSIC MEDICINE -A QUESTIONNAIRE-BASED STUDY
DOI:
https://doi.org/10.48165/jfmt.2024.41.2.22Keywords:
Artificial intelligence, Forensic Medicine, machine learning, neural networkAbstract
Forensic Medicine traditionally relies on manual analysis by Forensic doctors, which can be time-consuming and influenced by personal biases. However, technology such as Artificial Intelligence (AI) has introduced new possibilities to this field. The study explores how teaching faculty and post graduate students of Forensic Medicine in selected institutions within India, perceive and utilize artificial intelligence in Forensic investigations. After review of articles regarding the uses of artificial intelligence in Forensic discipline and practices, a questionnaire was created, and distributed to teaching faculty and postgraduate students of Forensic Medicine for insights into their understanding and perspectives on artificial intelligence. The study participants consisted of Forensic Medicine teaching faculty of 61 in numbers and 35 postgraduate students, a total of 96 participants in which various perceptions about Artificial intelligence were explored. The majority of participants acknowledged the potential of Artificial intelligence to enhance efficiency in Forensic investigations, envisioning its use in conferences, research, solving complex cases,and highlighted its application in virtopsy, DNA analysis and recognizing injury patterns. Nearly 50% of the participants disagreed regarding inaccuracy of Artificial intelligence application in Forensic investigations. The cost for implication of Artificial intelligence in Forensic investigations was considered expensive by nearly 70% of the participants. More than half of the participants lack knowledge regarding Artificial intelligence application in drug abuse, detecting traumatic brain injury. For effectively integrating Artificial intelligence into Forensic practice, awareness of Artificial intelligence application in Forensic research is essential. A clear guideline is required to uphold ethical principles in the use of Artificial intelligence in teaching and learning. More so, exploring Artificial intelligence usage to gain knowledge could help reduce workload, time constraint and improve precision and accuracy in Forensic investigation.
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Thurzo A, Kosnáèová HS, Kurilová V, Kosme¾ S, Beòuš R, Moravanský N, Kováè P, Kuracinová KM, Palkoviè M, Varga I. Use of advanced artificial intelligence in forensic medicine, forensic anthropology and clinical anatomy. InHealthcare 2021 Nov 12 (Vol. 9, No. 11, p. 1545). MDPI.
Piraianu AI, Fulga A, Musat CL, Ciobotaru OR, Poalelungi DG, Stamate E, Ciobotaru O, Fulga I. Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine. Diagnostics. 2023 Sep 19;13(18):2992.
Kotsyubynska YZ, Kozan NM, Zelenchuk GM, Voloshinovich VM, Kotsyubynsky AO. Artificial Neural Networks in Forensic Medicine. Medico-Legal Update. 2021 Jul 1;21(3).
Dou P, Shah SK, Kakadiaris IA. End-to-end 3D face reconstruction with deep neural networks. Inproceedings of the IEEE conference on computer vision and pattern recognition 2017 (pp. 5908-5917).
Mahmoud AT, Awad WA, Behery G, Abouhawwash M, Masud M, Aljuaid H, Ebada AI. An Automatic Deep Neural Network Model for Fingerprint Classification. Intelligent Automation & Soft Computing. 2023 May 1;36(2):2007-23.
Matsuda S, Yoshimura H. Personal identification with artificial intelligence under COVID-19 crisis: a scoping review. Systematic Reviews. 2022 Dec;11(1):1-6.
Khanagar SB, Vishwanathaiah S, Naik S, Al-Kheraif AA, Divakar DD, Sarode SC, Bhandi S, Patil S. Application and performance of artificial intelligence technology in forensic odontology–A systematic review. Legal Medicine. 2021 Feb 1;48:101826.
Pinchi V, Pradella F, Buti J, Baldinotti C, Focardi M, Norelli GA. A new age estimation procedure based on the 3D CBCT study of the pulp cavity and hard tissues of the teeth for forensic purposes: A pilot study. Journal of forensic and legal medicine. 2015 Nov 1;36:150-7.
Wankhade TD, Ingale SW, Mohite PM, Bankar NJ, Wankhade T, Ingale S, MOHITE P. Artificial intelligence in forensic medicine and toxicology: The future of forensic medicine. Cureus. 2022 Aug 25;14(8).
Jha N, Shankar PR, Al-Betar MA, Mukhia R, Hada K, Palaian S. Undergraduate medical Students’ and Interns’ knowledge and perception of artificial intelligence in medicine. Advances in Medical Education and Practice. 2022 Dec 31:927-37.
Sassis L, Kefala-Karli P, Sassi M, Zervides C. Exploring medical students’ and faculty’s perception on artificial intelligence and robotics. A questionnaire survey. Journal of Artificial Intelligence for Medical Sciences. 2021 May 5;2(1-2):76-84.
Boillat T, Nawaz FA, Rivas H. Readiness to embrace artificial intelligence among medical doctors and students: questionnaire-based study. JMIR medical education. 2022 Apr 12;8(2):e34973.
Liu DS, Sawyer J, Luna A, Aoun J, Wang J, Boachie L, Halabi S, Joe B. Perceptions of US medical students on artificial intelligence in medicine: mixed methods survey study. JMIR Medical Education. 2022 Oct 21;8(4):e38325.
Wood EA, Ange BL, Miller DD. Are we ready to integrate artificial intelligence literacy into medical school curriculum: students and faculty survey.
Journal of medical education and curricular development. 2021 Jun;8:23821205211024078.
Truong NM, Vo TQ, Tran HT, Nguyen HT. Healthcare students’ knowledge, attitudes, and perspectives toward artificial intelligence in the southern Vietnam. Heliyon. 2023 Dec 1;9(12).
Gillissen A, Kochanek T, Zupanic M, Ehlers J. Medical students’ perceptions towards digitization and artificial intelligence: a mixed-methods study. InHealthcare 2022 Apr 13 (Vol. 10, No. 4, p. 723). MDPI.
Blanco-Gonzalez A, Cabezon A, Seco-Gonzalez A, Conde-Torres D, Antelo-Riveiro P, Pineiro A, Garcia Fandino R. The role of ai in drug discovery: challenges, opportunities, and strategies. Pharmaceuticals. 2023 Jun 18;16(6):891.
Kumari D, Swetapadma A. Analysis of alcohol abuse using improved artificial intelligence methods. InJournal of Physics: Conference Series 2021 Aug 1 (Vol. 1950, No. 1, p. 012003). IOP Publishing.
Hibi A, Jaberipour M, Cusimano MD, Bilbily A, Krishnan RG, Aviv RI, Tyrrell PN. Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet?. Medicine. 2022 Nov 25;101(47):e31848.
Alouani AT, Elfouly T. Traumatic brain injury (TBI) detection: past, present, and future. Biomedicines. 2022 Oct 3;10(10):2472.
Barash M, McNevin D, Fedorenko V, Giverts P. Machine learning applications in forensic DNA profiling: A critical review. Forensic Science International: Genetics. 2023 Dec 1:102994.
Vilhekar RS, Rawekar A. Artificial Intelligence in Genetics. Cureus. 2024 Jan 10;16(1).
Kozan NM, YuZ K, Zelenchuk GM. Using the artificial neural networks for identification unknown person. IOSR Journal of dental and medical sciences. 2017 Apr;16(4):107-13.
O’Sullivan S, Holzinger A, Zatloukal K, Saldiva P, Sajid MI, Wichmann D. Machine learning enhanced virtual autopsy. Autopsy & case reports. 2017 Oct;7(4):3.
O’Sullivan S, Heinsen H, Grinberg LT, Chimelli L, Amaro E, do Nascimento Saldiva PH, Jeanquartier F, Jean-Quartier C, da Graça Morais Martin M, Sajid MI, Holzinger A. The role of artificial intelligence and machine learning in harmonization of high-resolution post-mortem MRI (virtopsy) with respect to brain microstructure. Brain informatics. 2019 Dec;6(1):1-2.