Assess the capabilities of AI-based large language models (AI-LLMs) in interpreting histopathological slides and scientific figures: performance evaluation study (Preprint)

Abstract

BACKGROUND Interpreting histopathology slides and scientific figures requires specialized skills and knowledge. Pathologists analyze various tissues and cells, while the general population often struggles with the technical information in scientific figures. Artificial intelligence-based large language models (AI-LLMs) can simplify these processes by providing clearer explanations. OBJECTIVE This study explores the capabilities AI-LLMs in interpreting histopathology slides and scientific figures. The objective is to assess the value of AI LLMs in medical applications and scientific education. METHODS The study was divided into two parts: interpreting histopathology slides and scientific figures. Six histopathology images and six scientific figures were tested on each of the three most frequently used chatbots (ChatGPT-4, Gemini Advanced, and Copilot). Responses from the chatbots were coded and blindly examined by expert raters using five parameters—relevance, clarity, depth, focus, and coherence—on a 5-point Likert scale. Statistical analysis included one-way ANOVA and multiple linear regression. RESULTS ChatGPT-4 outperformed Gemini Adv and Copilot in both histopathology and scientific image interpretation, with significantly higher scores across all parameters (P<.001). High homogeneity among raters validated these findings. ChatGPT-4's superior performance may be due to its advanced algorithms, extensive training data, specialized modules, and user feedback. CONCLUSIONS ChatGPT-4 excels in interpreting histopathology and scientific images, which may lead to improving diagnostic accuracy, clinical decision-making, and reducing pathologists' workload. It also benefits education by enhancing students' understanding of complex images and promoting interactive learning. ChatGPT-4 shows a significant potential to improve patient care and enrich student learning.