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Adequacy of prostate cancer prevention and screening recommendations provided by an artificial intelligence-powered large language model

  • Giuseppe Chiarelli,
  • Alex Stephens,
  • Marco Finati,
  • Giuseppe Ottone Cirulli,
  • Edoardo Beatrici,
  • Dejan K. Filipas,
  • Sohrab Arora,
  • Shane Tinsley,
  • Mahendra Bhandari,
  • Giuseppe Carrieri,
  • Quoc-Dien Trinh,
  • Alberto Briganti,
  • Francesco Montorsi,
  • Giovanni Lughezzani,
  • Nicolò Buffi,
  • Craig Rogers,
  • Firas Abdollah

摘要

Purpose

We aimed to assess the appropriateness of ChatGPT in providing answers related to prostate cancer (PCa) screening, comparing GPT-3.5 and GPT-4.

Methods

A committee of five reviewers designed 30 questions related to PCa screening, categorized into three difficulty levels. The questions were formulated identically for both GPTs three times, varying the prompts. Each reviewer assigned a score for accuracy, clarity, and conciseness. The readability was assessed by the Flesch Kincaid Grade (FKG) and Flesch Reading Ease (FRE). The mean scores were extracted and compared using the Wilcoxon test. We compared the readability across the three different prompts by ANOVA.

Results

In GPT-3.5 the mean score (SD) for accuracy, clarity, and conciseness was 1.5 (0.59), 1.7 (0.45), 1.7 (0.49), respectively for easy questions; 1.3 (0.67), 1.6 (0.69), 1.3 (0.65) for medium; 1.3 (0.62), 1.6 (0.56), 1.4 (0.56) for hard. In GPT-4 was 2.0 (0), 2.0 (0), 2.0 (0.14), respectively for easy questions; 1.7 (0.66), 1.8 (0.61), 1.7 (0.64) for medium; 2.0 (0.24), 1.8 (0.37), 1.9 (0.27) for hard. GPT-4 performed better for all three qualities and difficulty levels than GPT-3.5. The FKG mean for GPT-3.5 and GPT-4 answers were 12.8 (1.75) and 10.8 (1.72), respectively; the FRE for GPT-3.5 and GPT-4 was 37.3 (9.65) and 47.6 (9.88), respectively. The 2nd prompt has achieved better results in terms of clarity (all p < 0.05).

Conclusions

GPT-4 displayed superior accuracy, clarity, conciseness, and readability than GPT-3.5. Though prompts influenced the quality response in both GPTs, their impact was significant only for clarity.