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

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.