What question did this study set out to answer?

The framework aims to enhance diagnostic reasoning in pathology through multimodal approaches.

March 10, 2026Open Access

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.

Abstract

By uniting visual understanding with reasoning, our framework provides a promising approach for clinically trustworthy artificial intelligence. This framework helps bridge the gap between opaque classifiers and auditable systems, suggesting a viable path toward evidence-linked interpretation in medical workflows.

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