Deep Learning in Medicine resources & Study Group

Part 1 (2019)
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Hey Guys

Thanks for creating this sub-group. Based on the lesson 1 of Part 1 course, I have done three independent projects and wrote three articles. Here is the link:

  1. Malaria Cell detection
    https://medium.com/@abhikjha/medical-images-use-cases-of-deep-learning-1b40d869ca17

  2. Pneumonia Chest X-rays
    https://medium.com/@abhikjha/medical-images-use-cases-of-deep-learning-part-2-c5df16f77ab1

  3. Cancer cells detection
    https://medium.com/@abhikjha/medical-images-use-cases-of-deep-learning-part-3-2ce12b0b41fe

Any feedback and comments will be welcome

Thanks and Regards
AJ

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Added my small work! Thanks for creating this group!

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Guys, anyone from fastai community has done any work on ECG, Cardiac Arrhythmia images using fastai tools? I would love to take some inspirations from their works and achievements.

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I have heard people doing 1D convolution on the chart raw data, but not the image.

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Hey @PegasusWithoutWinds and @pierreguillou does the shared google drive exist? If it does, please provide a link to it

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If there is no link, then sadly this probably does not exist. Sadā€¦

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I started working on mitosis detection in breast histopathology Image using MITOS dataset. How should I make progress? Any help will be appreciable.

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You can threat ECG Signal like an audio one: there is some post on the deep learning with audio thread :wink:

Deep Learning with Audio Thread?

Deep Learning with Audio Thread?

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I did a bit of ECG interpretation work a few months ago, using resnet

@ste Iā€™m interested in that audio approach.

Iā€™m working on something else now. Trying to correlate the success of the endoscopy to the description of the procedure.

Having trouble understand exactly what my model is predicting.

NLP Question.

Iā€™ve got a pretty simple model trying to correlate a short sentence which has been written about an endoscopy to a label which indicates whether the endoscopy was successful at visualizing the whole colon or not.

nbviewer.jupyter.org

Jupyter Notebook Viewer

Check out this Jupyter notebook!

**When my model makes a prediction, sometimes it takes the same input (e.g the terminal ileum) and makes different predictions **

image.png
image.png760Ɨ34 991 Bytes

image.png
image.png763Ɨ28 931 Bytes

I really canā€™t make sense of that output. Can someone with NLP experience help me out here?

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I added the kaggle retinopathy competitions to the wiki. There was one 4 years ago and the current one is finishing in 3 weeks. Very interesting problem!

I wish we had better tools to classify this type of image. Transfer learning using models that were trained on cats and dogs just doesnā€™t seem ideal!

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Thanks for detailed sources but I am willing to use deep learning in statistical areas especially related to sports.

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Hi,

I am working on a relatively old dataset, ISIC 2016 skin lesion classification, and I am considering to try out transfer learning using model zoo/models pretrained on medical images but not aware if there is any which I can try out. I am aware of using other datasets to increase training images, but specifically I want to try it on pretrained models on medical images. Any kinds of suggestions would be helpful.

Thanks!

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This is great!

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Hello guys.

Iā€™d like to share our work, sorry for a bit of self PR))

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Hi seb!
You did put it into the wiki. Where is that?
Regards
Rolf

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By ā€œwikiā€, I meant the top post of this thread (under ā€œcompetitionsā€), which is modifiable by everyone

Edit: added the MIMIC-CXR Database

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I have download the ecg data used in a Jan 2018 publication. The EKG is in a file with .ecg extension.
Any advice on how to open and handle these files in Colab. Does Resnet treat these as image files? I tried opening these files with a photo app on Windows and they wonā€™t open. There is an online app for viewing ECGs but it requires a license even though it says it is free.

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Just thought Iā€™d pop back in and say this thread is fantastic. Iā€™ve been sharing some of these articles with the doctors in Melbourne and they really appreciate it. Look forward to hearing from others trying to move forward in this vein.

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Hey guys - looking to start a project to use low dose CT to high dose CT but a beginner with using DICOMs and implementing them into code. Is there a step by step guide to do this? Thanks!

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These are the resources that helped me when I was a DICOM beginner:

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