International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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AI-powered Differentiation of Accidental and Intentional Burn Injuries: A Forensic and Clinical Approach

Author(s) Ms. Prajkta Thakur Thakur, Ms. Prakriti Kaul, Ms. Sanjna Thakur, Ms. Muskan Bhatnoo
Country India
Abstract Burn injuries continue to be a major worldwide health issue, leading to considerable rates of illness and death. It is essential to distinguish between accidental and intentional burns for effective clinical management and forensic investigations.This research investigates how artificial intelligence (AI) can be used to classify burn injuries accurately, using forensic and clinical parameters. Models driven by AI, which employ machine learning and deep learning techniques, can examine burn patterns, injury depth and distribution to differentiate between unintentional burns (like scalds, contact burns, or flame burns) as well as those that are purposefully caused (e.g., chemical assaults, planned burns, or forced immersion). The project aims to develop an AI-powered framework that enhances diagnostic precision, facilitates forensic investigation, and aids medical professionals in taking prompt action.By using the AI model on real burn cases and assessing its ability to differentiate between different injury kinds, the study validates the model's efficacy. the integration of artificial intelligence (AI) into clinical and forensic processes has promise for revolutionizing the management of burn injuries, leading to better medical care, legal actions, and victim support.
Keywords Predictive analytics, burn pattern recognition, accidental and intentional burn injuries, machine learning, artificial intelligence (AI), and legal interventions.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 4, July-August 2025
Published On 2025-07-07
DOI https://doi.org/10.36948/ijfmr.2025.v07i04.50202
Short DOI https://doi.org/g9s9dg
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