Venue: MIDL 2023 Short_Paper_Track

Reviews:

final_score: rating: 8: Top 50% of accepted papers, clear accept
review_content: This paper evaluates different language models, pre-trained on general corpuses, for disease detection when image+text are available. The authors focus on rare disease, which are difficult to generalize to and have no training data.

While I am not quite sure that the term of zero-shot is right, clearly the general models are able to reach very impressive performances "out of the box", even better than the authors' domain specific model (CheXzero).
review_title: Effective use of pretrained language models

final_score: rating: 6: Marginally above acceptance threshold
review_content: The basic premise of the paper is good but it has not been explained properly. 
review_title: Paper 120 review

Decision: Accept(Poster)