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ChatGPT 4.0 and algor in generating concept maps: an observational study.

Antonino Maniaci1,2,3,4, Caterina Gagliano5, Valerio Salerno5

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European Archives of Oto-Rhino-Laryngology : Official Journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : Affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
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Summary

Two AI systems, ChatGPT 4.0 and Algor, show potential for generating concept maps from otolaryngology clinical practice guidelines, with varied strengths in knowledge representation and visual presentation.

Keywords:
Artificial intelligenceConcept mappingKnowledge representationMedical educationOtolaryngology guidelines

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Knowledge Representation

Background:

  • Evaluating AI performance in medical knowledge synthesis.
  • Utilizing concept maps for understanding clinical practice guidelines.

Purpose of the Study:

  • To compare ChatGPT 4.0 and Algor in generating concept maps from otolaryngology guidelines.
  • Assess AI-generated concept maps based on expert evaluations.

Main Methods:

  • Concept maps generated by AI from AAO-HNSF guidelines.
  • Expert review using the AI-Map questionnaire.
  • Statistical analysis with Chi-square tests and Kendall's tau.

Main Results:

  • ChatGPT 4.0 excelled in cross-connections and layout (Rhinoplasty).
  • Algor demonstrated strengths in main themes and concept distinction (BPVV, Tympanostomy Tubes).
  • Significant differences noted in dynamic nature representation and overall usefulness for H&N Masses guidelines.

Conclusions:

  • AI systems show promise for automating concept map creation from medical guidelines.
  • Performance varies by AI model, medical topic, and evaluation criteria.
  • Further research needed to optimize AI for medical education and knowledge representation.