AI may stumble on acne diagnosis - Summary - MDSpire
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AI may stumble on acne diagnosis

  • By

  • Andrea Surnit

  • October 2, 2026

  • 3 min

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Objective:

To evaluate the appropriateness of responses generated by ChatGPT-5 for common acne-related questions.

Approach:
  • Study Design: A cross-sectional observational study using 25 acne-related questions categorized into skin care routine, nutrition and lifestyle, diagnosis and general information, and treatment and medications.
  • Response Evaluation: Each question was submitted to ChatGPT-5 in three independent sessions, generating 75 responses, which were classified by three dermatologists as appropriate or inappropriate.
Key Findings:
  • 65% of responses were classified as appropriate.
  • Appropriateness was highest for skin care (83%) and lowest for diagnosis and general information (33%).
  • Misleading information was the most common reason for inappropriate ratings.
Limitations:
  • The study was limited to acne, affecting generalizability to other dermatologic conditions.
  • Binary classification may not capture intermediate degrees of appropriateness.
  • Low inter-rater agreement among dermatologists raises concerns about the consistency of evaluations.
Sources:

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