Illustration of GSCo’s two core collaboration mechanisms. In Mixture-of-Expert Diagnosis (MoED, top), multiple lightweight specialist models are independently trained on the downstream dataset. During inference, the test image is fed to all specialist m (IMAGE)
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Illustration of GSCo’s two core collaboration mechanisms. In Mixture-of-Expert Diagnosis (MoED, top), multiple lightweight specialist models are independently trained on the downstream dataset. During inference, the test image is fed to all specialist models, and their predictions are incorporated into MedDr’s prompt as structured references. In Retrieval-Augmented Diagnosis (RAD, bottom), an embedding model encodes each image–text pair into a medical database. At inference, the test image’s embedding is used to retrieve the most similar cases, whose metadata are subsequently provided to MedDr as additional contextual evidence.
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