Sign inGet started
Paper · arXiv

MedCORE: Criteria-Grounded Clinical Reasoning for Interpretable Medical Image Diagnosis

Clinical diagnosis is inherently a structured reasoning process, yet existing deep learning models often bypass this structure by mapping image features directly to disease labels without explicitly interrogating the morphological and textural criteria that clinicians systematically evaluate. This limits diagnostic transparency and may compromise safe clinical deployment. We present MedCORE (Medical Criteria-Oriented Reasoning and Evidence), a structured diagnostic framework that operationalizes clinical reasoning within a vision-language architecture. For each input image, MedCORE decomposes the diagnostic process into clinically defined criteria, spatially localizes each criterion to di...

AuthorsAsim Khan, Samee Ullah Khan, Dwarikanath Mahapatra
Primary categorycs.CV
Published6 October 2026
Last updated at source6 October 2026
cs.CVcs.AI
Embed this entry
<iframe src="https://silytics.si/embed/item/e203fbb1-7d89-4bdd-8a02-c03d92cb1352" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 2 days

0 now. Counts as reported by the source, snapshotted daily by Silytics.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.