Adaptive diagnostic reasoning framework for pathology with multimodal large language models

Key Points

• The framework aims to enhance diagnostic reasoning in pathology through multimodal approaches.
• Developed a framework integrating visual data and reasoning processes.
• Implemented artificial intelligence to improve interpretation accuracy.
• Focused on creating auditable systems for clinical use.
• Demonstrated improved trustworthiness of AI in diagnostic processes.
• Provided a clear path for integrating evidence-based interpretations.
• Highlighted the gap bridged between opaque AI classifiers and transparent systems.