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Artificial intelligence as a tool for data extraction is not fully reliable compared to manual data extraction.

Baraa Daraqel1, Amer Owayda2, Haris Khan3

  • 1Department of Orthodontics, Oral Health Research and Promotion Unit, Al-Quds University, Jerusalem, Palestine.

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Summary

Artificial intelligence (AI) tools show promise for extracting straightforward data in systematic reviews, but human oversight is crucial for complex information to ensure accuracy and reliability in clinical evidence.

Keywords:
AIData extractionSystematic review

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Area of Science:

  • Orthodontics
  • Biomedical Informatics
  • Data Science

Background:

  • Systematic reviews are essential for evidence-based practice but involve time-consuming and error-prone data extraction.
  • Automating data extraction can potentially improve efficiency and reduce errors in systematic reviews.

Purpose of the Study:

  • To evaluate the agreement between artificial intelligence (AI)-based and human data extraction methods in orthodontic systematic reviews.
  • To assess the reliability of AI tools for extracting various data points from scientific literature.

Main Methods:

  • A systematic search identified 300 orthodontic studies published between 2019 and 2024.
  • Two independent reviewers extracted data manually and using Microsoft Bing AI.
  • Agreement was assessed using interclass correlation and Kappa statistics, comparing AI and human extraction.

Main Results:

  • AI demonstrated slight differences for publication years and study designs, which were not statistically significant.
  • AI was less effective in extracting complex variables like study design details (P = 0.017) and number of centers (P < 0.001).
  • Agreement ranged from slight (0.16 for study design type) to substantial/perfect (0.65-1.00 for most other variables).

Conclusions:

  • AI-based data extraction is effective for simple variables but not fully reliable for complex data.
  • Human input remains essential for ensuring accuracy and completeness in systematic reviews.
  • AI tools can enhance efficiency, but human supervision is vital for maintaining the integrity of clinical evidence.