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Updated: Jan 16, 2026

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Leveraging chatgpt' s advanced data analysis for forensic science research and applications.

Jian Li1,2, Shu-Rui Zhang1,2, Yu Gao1,2

  • 1School of Forensic Medicine, Shanxi Medical University, 98, University Street, Wujinshan Town, Yuci District, Jinzhong Shanxi Province, 030604, People's Republic of China.

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Keywords:
ADAChatGPTLLMMachine learning

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Area of Science:

  • Forensic Science
  • Machine Learning
  • Artificial Intelligence

Background:

  • Machine learning (ML) aids forensic decision-making but is complex.
  • Developing ML models is challenging for forensic research and practice.

Purpose of the Study:

  • Assess the efficacy of autonomous machine learning models for Advanced Data Analysis (ADA).
  • Evaluate ADA's performance on diverse forensic tasks like postmortem interval (PMI), injury time, and sudden cardiac death (SCD) prediction.

Main Methods:

  • Utilized ChatGPT-4 based Advanced Data Analysis (ADA) tools.
  • ADA autonomously performed data standardization and optimal ML model selection.
  • Compared ADA's predictive performance against models built by professional data analysts.

Main Results:

  • ADA demonstrated robust predictive performance across various datasets.
  • No statistically significant differences were found between ADA and expert-developed models.
  • ADA successfully handled diverse data types for forensic applications.

Conclusions:

  • ChatGPT ADA simplifies ML model construction for forensic applications.
  • ADA offers a prospective tool for implementing ML in forensic research and practice.
  • ADA should supplement, not replace, researchers in forensic science.