Turkiye Klinikleri Journal of Ophthalmology

.: ORIGINAL RESEARCH
Assessment of the Performance of ChatGPT-4o, Claude 3.5 Sonnet, and Google Gemini 2.0 Flash on Image-Based Ocular Oncology and Pathology Questions: A Cross-Sectional Research
ChatGPT-4o, Claude 3.5 Sonnet ve Google Gemini 2.0 Flash'in Görüntü Tabanlı Oküler Onkoloji ve Patoloji Sorularındaki Performansının Değerlendirilmesi: Kesitsel Araştırma
Süleyman DEMİRa , İsmail Cem TÜRKEŞb
aAdana 5 Ocak State Hospital, Clinic of Ophthalmology, Adana, Türkiye
bGülhane Training and Research Hospital, Clinic of Ophthalmology, Ankara, Türkiye
Turkiye Klinikleri J Ophthalmol. 2025;34(4):175-82
doi: 10.5336/ophthal.2025-110083
Article Language: EN
Full Text
ABSTRACT
 Objective: This study aimed to evaluate the diagnostic performance of 3 flagship models from 3 different companies, Chat Generative Pre-trained Transformer-4 Omni (ChatGPT-4o), Claude 3.5 Sonnet, and Gemini 2.0 Flash, on image-based questions in ocular oncology and pathology to investigate potential differences between these models, and their clinical utility. Material and Methods: Fifty multiple-choice, imagebased questions were randomly selected from 312 questions in the field of ocular oncology and pathology from the OphthoQuestions (www.ophthoquestions.com) database. The answers given to the questions were compared with the answer key and recorded as correct or incorrect. ChatGPT-4o, Claude 3.5 Sonnet and Gemini 2.0 Flash models, which have the ability to process images in large language models (LLMs), were included in the study. Cochran's Q test was applied to compare the performance of the 3 LLMs and McNemar's test was used in pairwise comparisons. Results: There was a statistically significant difference between all 3 LLMs (p=0.001, Cochran's Q test). Claude 3.5 sonnet showed the highest accuracy by correctly identifying 84% of the questions, followed by ChatGPT-4o with 80% and Gemini 2.0 with 62%. In the pairwise comparisons, Claude 3.5 sonnet and ChatGPT-4o were found to be statistically superior to Gemini 2.0 Flash model (p=0.002, p=0.004, respectively). There was no significant difference between Claude 3.5 and ChatGPT-4o (p=0.727, McNemar test). Conclusion: Our results indicate that Claude 3.5 Sonnet and GPT-4o outperform Gemini 2.0 Flash in diagnostic accuracy for ocular oncology and pathology. While LLMs show promise in this field, they require evaluation with larger datasets, and their accuracy must be improved before they can be clinically implemented.

Keywords: ChatGPT-4o; Claude-3.5 Sonnet; Gemini 2.0 Flash; ocular oncology; image processing
ÖZET
 Amaç: Bu çalışmanın amacı, 3 farklı şirketten 3 önde gelen büyük dil modeli Chat Generative Pre-trained Transformer-4 Omni (ChatGPT-4o), Claude-3.5 Sonnet ve Gemini 2.0 Flash'ın oküler onkoloji ve patoloji alanındaki görüntü tabanlı sorularda tanısal performansını değerlendirmek ve bu modeller arasındaki potansiyel farkları ile pratik kullanım için uygunluklarını araştırmaktır. Gereç ve Yöntemler: OphthoQuestions (www.ophthoquestions.com) veritabanından oküler onkoloji ve patoloji alanında yer alan 312 sorudan rastgele seçilen 50 çoktan seçmeli, görüntü tabanlı soru kullanılmıştır. Soruların yanıtları, doğru yanıt anahtarıyla karşılaştırılmış ve doğru ya da yanlış olarak kaydedilmiştir. Çalışmaya, güncel ve görüntü işleme özelliği olan büyük dil modelleri [large language models (LLMs)] ChatGPT-4o, Claude 3.5 Sonnet ve Gemini 2.0 Flash dâhil edilmiştir. 3 LLMs modellerinin performansını karşılaştırmak için Cochran's Q testi, 2'li karşılaştırmalar için ise McNemar testi kullanılmıştır. Bulgular: Üç LLMs arasında istatistiksel olarak anlamlı bir fark bulunmuştur (p=0,001, Cochran's Q testi). Claude 3.5 Sonnet, soruların %84'ünü doğru cevaplayarak en yüksek doğruluk oranını göstermiş, bunu %80 doğrulukla ChatGPT-4o ve %62 doğrulukla Gemini 2.0 Flash takip etmiştir. İkili karşılaştırmalarda, Claude 3.5 Sonnet ve ChatGPT-4o, Gemini 2.0 Flash modeline karşı istatistiksel olarak üstün bulunmuştur (sırasıyla p=0,002, p=0,004). Claude 3.5 Sonnet ile ChatGPT-4o arasında ise anlamlı bir fark bulunmamıştır (p=0,727, McNemar test). Sonuç: Sonuçlarımız, Claude 3.5 Sonnet ve GPT4o'nun oküler onkoloji ve patoloji alanında tanısal doğruluk açısından Gemini 2.0 Flash'ı geride bıraktığını göstermektedir. LLMs bu alanda umut vaat etse de, daha büyük veri setleriyle eğitilmesi ve doğruluklarının klinik kullanım için iyileştirilmesi gerekmektedir.

Anahtar Kelimeler: ChatGPT-4o; Claude 3.5 Sonnet; Gemini 2.0 Flash; oküler onkoloji; görüntü işleme
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