MedCLIP
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EMNLP'22 | MedCLIP: Contrastive Learning from Unpaired Medical Images and Texts
In the paper, the pre-training and evaluation datasets all were of X-ray modality. Do you have any information about how it will perform on other radiology modalities like Mammographs, MRI?...
hello, First, thanks for creating MedCLIP. It's a great job. In your published paper on this work, experiments were done and the answer to Q3: Does MedCLIP lead to better...
where is The knowledge extraction module in code?thanks!!!!What specific model are they using?
Hi, first of all: thanks for creating MedCLIP. It seems to be an amazing library. I'd like to embed several hundreds of images with the MedCLIPProcessor. However my GPU memory...
value in demo_from_pretrained_and_encode.ipynb is 0.2560, 0.6394 but got 0.1729, 0.3899 classify result also wrong i download weight from url in txt file,other weights are auto downloaded,is this way right?
Firstly, thanks for your great job!! It brought me a huge convenience when using it in downstream tasks. Besides, I want to know does your model support different languages when...
Hello, Thanks for your amazing work! May I ask how to obtain the sentence-label.csv from the MIMIC-CXR dataset? Are you using the concatenation of impression and findings as a whole...
Hi! Do you consider releasing your MIMIC zero-shot classification splits? Thanks.
When I tried the [As simple as using CLIP](https://github.com/RyanWangZf/MedCLIP#as-simple-as-using-clip) you provided, I got the following error ``` Traceback (most recent call last): File "main.py", line 26, in outputs = model(**inputs)...