mahmoodlab / survpath Goto Github PK

Your thesis visualisation work is great, could you please share the visualisation code?

Hi,

Thanks for the interesting work. Can you please share the total number of parameters or at least an estimation?
I may have misunderstood it, but I assume that there is a separate SNN block for each pathway. So, If we have 330 pathways here, the pathway tokenizer will have at least 330256256 parameters which is about 21 million. I appreciate your clarification.

Thanks

Thanks for sharing the code, I have a question regarding the experimental setup.1. Is the C-index value under 5-fold cross-validation in the article obtained as the highest C-index value for each fold or the corresponding C-index value when the loss per fold drops to the minimum?2. What criterion are you basing on to save the model for each fold training? Maximum C-index or minimum loss?

Dear authors,

I found your work on transcriptomics, histology, and multimodal fusion for classification tasks to be quite interesting. I would like to know more about the folder structure you used in your experiments. Specifically, I'm interested in understanding how you organized the different data modalities and their corresponding files.

Could you kindly provide some information or details regarding the folder structure you employed in your study? It would greatly help me in better understanding and replicating your experiments.