{ "id": 369103, "title": "πŸ† Winning solutions from previous RSNA challenges", "url": "/competitions/rsna-breast-cancer-detection/discussion/369103", "author_name": "Radek Osmulski", "post_date": "2022-11-29T00:05:29.366000", "votes": 120, "comment_count": 12, "views": 0, "content": "

Hey!

\n

Very excited for this competition launch! πŸ™‚ Here are short summaries of previous RSNA competitions with links to winning solutions to drow inspiration from!

\n

RSNA-MICCAI Brain Tumor Radiogenomic Classification

\n

Please note: this competition didn't go that well due to the reasons @theoviel so eloquently outlines here

\n\n

Notable mention: Very nice EfficientNet3d code for those training models outside of Kaggle

\n

RSNA 2022 Cervical Spine Fracture Detection

\n\n

Notable mention: 5th place solution (Team Speedrun) by @christofhenkel (great outline, visualization and a link to code on github! ❀️‍πŸ”₯)

\n

RSNA-MICCAI Brain Tumor Radiogenomic Classification

\n\n

Notable mention: A brilliant EDA with animated visualizations

\n

RSNA STR Pulmonary Embolism Detection

\n\n

Notable mention: Fast GPU Experimentation Pipeline by @cdeotte

\n

RSNA Intracranial Hemorrhage Detection

\n\n

Notable mention: A summary post with links to code for each of the gold medal solutions by @rohanrao

\n

RSNA Pneumonia Detection Challenge

\n\n

Other resources you might find useful:

\n\n

Thank you for reading! Best of luck in the challenge!

", "messages": [ { "id": 2047674, "postDate": "2022-11-29T00:05:29.367Z", "content": "

Hey!

\n

Very excited for this competition launch! πŸ™‚ Here are short summaries of previous RSNA competitions with links to winning solutions to drow inspiration from!

\n

RSNA-MICCAI Brain Tumor Radiogenomic Classification

\n

Please note: this competition didn't go that well due to the reasons @theoviel so eloquently outlines here

\n\n

Notable mention: Very nice EfficientNet3d code for those training models outside of Kaggle

\n

RSNA 2022 Cervical Spine Fracture Detection

\n\n

Notable mention: 5th place solution (Team Speedrun) by @christofhenkel (great outline, visualization and a link to code on github! ❀️‍πŸ”₯)

\n

RSNA-MICCAI Brain Tumor Radiogenomic Classification

\n\n

Notable mention: A brilliant EDA with animated visualizations

\n

RSNA STR Pulmonary Embolism Detection

\n\n

Notable mention: Fast GPU Experimentation Pipeline by @cdeotte

\n

RSNA Intracranial Hemorrhage Detection

\n\n

Notable mention: A summary post with links to code for each of the gold medal solutions by @rohanrao

\n

RSNA Pneumonia Detection Challenge

\n\n

Other resources you might find useful:

\n\n

Thank you for reading! Best of luck in the challenge!

", "rawMarkdown": "Hey! \n\nVery excited for this competition launch! πŸ™‚ Here are short summaries of previous RSNA competitions with links to winning solutions to drow inspiration from!\n\n# [RSNA-MICCAI Brain Tumor Radiogenomic Classification](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/overview)\n\n**Please note:** this competition didn't go that well due to the reasons @theoviel so eloquently outlines [here](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/279820)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/281347)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/280033)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/287713)\n\n*Notable mention:* [Very nice EfficientNet3d code for those training models outside of Kaggle](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/262103)\n\n# [RSNA 2022 Cervical Spine Fracture Detection](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/overview)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/362607), [code](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/362787)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/365115)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/362643)\n\n*Notable mention:* [5th place solution (Team Speedrun)](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/363232) by @christofhenkel (great outline, visualization and a link to code on github! ❀️‍πŸ”₯)\n\n# [RSNA-MICCAI Brain Tumor Radiogenomic Classification](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification)\n\n* [1st place solution](https://www.kaggle.com/code/rinnqd/monai-simple-prediction-from-flair/notebook?scriptVersionId=74519212)\n* [2nd place solution](https://www.kaggle.com/code/minhnhatphan/rnsa-21-cnn-lstm-inference/notebook?scriptVersionId=69112809)\n* [3rd place solution](https://www.kaggle.com/code/cedricsoares/tf-efficientnet-transfer-learning-strat-split/notebook?scriptVersionId=77118556)\n\n*Notable mention:* [A brilliant EDA with animated visualizations](https://www.kaggle.com/code/ihelon/brain-tumor-eda-with-animations-and-modeling)\n\n# [RSNA STR Pulmonary Embolism Detection](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/194145)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/193401)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/193424)\n\n*Notable mention:* [Fast GPU Experimentation Pipeline](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/193402) by @cdeotte \n\n# [RSNA Intracranial Hemorrhage Detection](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/overview)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/117210)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/116760)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/117223)\n\n*Notable mention:* [A summary post with links to code for each of the gold medal solutions](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/117242) by @rohanrao\n\n# [RSNA Pneumonia Detection Challenge](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/overview)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/discussion/70421)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/discussion/70427)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/discussion/70632)\n\n### Other resources you might find useful:\n\n* [πŸ’‘ how to process DICOM images to PNGs](https://www.kaggle.com/code/radek1/how-to-process-dicom-images-to-pngs)\n* [πŸ“Š EDA + training a fast.ai model + submission πŸš€](https://www.kaggle.com/code/radek1/eda-training-a-fast-ai-model-submission)\n* [πŸ€– [fast.ai starter pack] train + inference πŸš€](https://www.kaggle.com/code/radek1/fast-ai-starter-pack-train-inference)\n* [πŸ“Έ Over 56GB of processed data, 5 different methods πŸ₯³](https://www.kaggle.com/competitions/rsna-breast-cancer-detection/discussion/371268)\n* [3 resources to get started with Computer Vision in this competition πŸš€πŸš€πŸš€](https://www.kaggle.com/competitions/rsna-breast-cancer-detection/discussion/369706)\n* [πŸ’‘ 6 Computer Vision tricks for faster training and better models πŸš€πŸš€πŸš€](https://www.kaggle.com/competitions/rsna-breast-cancer-detection/discussion/369155)\n\n\nThank you for reading! Best of luck in the challenge!", "votes": 120 }, { "id": 2052425, "postDate": "2022-12-02T07:34:11.107Z", "content": "

first time join, hope we can learn and have some experiment

", "rawMarkdown": "first time join, hope we can learn and have some experiment", "votes": 1 }, { "id": 2047984, "postDate": "2022-11-29T06:46:55.487Z", "content": "

thanks for sharing !

", "rawMarkdown": "thanks for sharing !", "votes": 1, "replies": [ { "id": 2048089, "postDate": "2022-11-29T08:12:29.170Z", "content": "

np at all πŸ™‚ glad that you found it useful!

", "rawMarkdown": "np at all πŸ™‚ glad that you found it useful! ", "votes": 1 } ] }, { "id": 2050454, "postDate": "2022-11-30T18:38:52.387Z", "content": "

That is just awesome Radek, such a valuable compilation! Been reading Meta Learning and your newsletter recently, you are really a great inspiration!

", "rawMarkdown": "That is just awesome Radek, such a valuable compilation! Been reading Meta Learning and your newsletter recently, you are really a great inspiration!", "votes": 2, "replies": [ { "id": 2050543, "postDate": "2022-11-30T20:25:46.440Z", "content": "

wow @jackonelli, thank you so much! πŸ™‚πŸ™extremely grateful and humbled you are finding these things useful πŸ™

", "rawMarkdown": "wow @jackonelli, thank you so much! πŸ™‚πŸ™extremely grateful and humbled you are finding these things useful πŸ™ " } ] }, { "id": 2050203, "postDate": "2022-11-30T15:28:35.900Z", "content": "

Thanks for the resources.

", "rawMarkdown": "Thanks for the resources.", "votes": 2, "replies": [ { "id": 2050544, "postDate": "2022-11-30T20:26:06.327Z", "content": "

np @gazu468! glad to be of help πŸ™‚

", "rawMarkdown": "np @gazu468! glad to be of help πŸ™‚ ", "votes": 1 } ] }, { "id": 2048797, "postDate": "2022-11-29T17:23:10.783Z", "content": "

I'm a beginner and this is very helpful, thanks!πŸ˜„

", "rawMarkdown": "I'm a beginner and this is very helpful, thanks!πŸ˜„", "votes": 2, "replies": [ { "id": 2049015, "postDate": "2022-11-29T21:16:31.887Z", "content": "

Perfect, mission accomplished then! 😊 Glad I could be of help! πŸ™Œ

", "rawMarkdown": "Perfect, mission accomplished then! 😊 Glad I could be of help! πŸ™Œ" } ] }, { "id": 2339654, "postDate": "2023-07-11T01:52:50.350Z", "content": "

This is really helpful. Thanks for sharing!

", "rawMarkdown": "This is really helpful. Thanks for sharing!" }, { "id": 2051538, "postDate": "2022-12-01T13:42:13.603Z", "rawMarkdown": "", "isDeleted": true }, { "id": 2134290, "postDate": "2023-02-07T21:44:34.187Z", "content": "

Thank you for sharing this information!

", "rawMarkdown": "Thank you for sharing this information!" } ], "comments": [ { "id": 2052425, "author_name": "LΓͺ ThΓ nh NghΔ©a", "author_url": "", "post_date": "2022-12-02T07:34:11.107000", "content": "

first time join, hope we can learn and have some experiment

", "votes": 1, "replies": [] }, { "id": 2047984, "author_name": "Khang Duong", "author_url": "", "post_date": "2022-11-29T06:46:55.487000", "content": "

thanks for sharing !

", "votes": 1, "replies": [ { "id": 2048089, "author_name": "Radek Osmulski", "author_url": "", "post_date": "2022-11-29T08:12:29.170000", "content": "

np at all πŸ™‚ glad that you found it useful!

", "votes": 1, "replies": [] } ] }, { "id": 2050454, "author_name": "MiOh", "author_url": "", "post_date": "2022-11-30T18:38:52.387000", "content": "

That is just awesome Radek, such a valuable compilation! Been reading Meta Learning and your newsletter recently, you are really a great inspiration!

", "votes": 2, "replies": [ { "id": 2050543, "author_name": "Radek Osmulski", "author_url": "", "post_date": "2022-11-30T20:25:46.440000", "content": "

wow @jackonelli, thank you so much! πŸ™‚πŸ™extremely grateful and humbled you are finding these things useful πŸ™

", "votes": 0, "replies": [] } ] }, { "id": 2050203, "author_name": "Gaju Ahmed", "author_url": "", "post_date": "2022-11-30T15:28:35.900000", "content": "

Thanks for the resources.

", "votes": 2, "replies": [ { "id": 2050544, "author_name": "Radek Osmulski", "author_url": "", "post_date": "2022-11-30T20:26:06.327000", "content": "

np @gazu468! glad to be of help πŸ™‚

", "votes": 1, "replies": [] } ] }, { "id": 2048797, "author_name": "GaH", "author_url": "", "post_date": "2022-11-29T17:23:10.783000", "content": "

I'm a beginner and this is very helpful, thanks!πŸ˜„

", "votes": 2, "replies": [ { "id": 2049015, "author_name": "Radek Osmulski", "author_url": "", "post_date": "2022-11-29T21:16:31.887000", "content": "

Perfect, mission accomplished then! 😊 Glad I could be of help! πŸ™Œ

", "votes": 0, "replies": [] } ] }, { "id": 2339654, "author_name": "Zilin Jiang szszS", "author_url": "", "post_date": "2023-07-11T01:52:50.350000", "content": "

This is really helpful. Thanks for sharing!

", "votes": 0, "replies": [] }, { "id": 2051538, "author_name": "", "author_url": "", "post_date": "2022-12-01T13:42:13.603000", "content": "", "votes": 0, "replies": [] }, { "id": 2134290, "author_name": "junseonglee11", "author_url": "", "post_date": "2023-02-07T21:44:34.187000", "content": "

Thank you for sharing this information!

", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "2047674": "Hey! \n\nVery excited for this competition launch! πŸ™‚ Here are short summaries of previous RSNA competitions with links to winning solutions to drow inspiration from!\n\n# [RSNA-MICCAI Brain Tumor Radiogenomic Classification](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/overview)\n\n**Please note:** this competition didn't go that well due to the reasons @theoviel so eloquently outlines [here](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/279820)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/281347)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/280033)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/287713)\n\n*Notable mention:* [Very nice EfficientNet3d code for those training models outside of Kaggle](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/262103)\n\n# [RSNA 2022 Cervical Spine Fracture Detection](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/overview)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/362607), [code](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/362787)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/365115)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/362643)\n\n*Notable mention:* [5th place solution (Team Speedrun)](https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/discussion/363232) by @christofhenkel (great outline, visualization and a link to code on github! ❀️‍πŸ”₯)\n\n# [RSNA-MICCAI Brain Tumor Radiogenomic Classification](https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification)\n\n* [1st place solution](https://www.kaggle.com/code/rinnqd/monai-simple-prediction-from-flair/notebook?scriptVersionId=74519212)\n* [2nd place solution](https://www.kaggle.com/code/minhnhatphan/rnsa-21-cnn-lstm-inference/notebook?scriptVersionId=69112809)\n* [3rd place solution](https://www.kaggle.com/code/cedricsoares/tf-efficientnet-transfer-learning-strat-split/notebook?scriptVersionId=77118556)\n\n*Notable mention:* [A brilliant EDA with animated visualizations](https://www.kaggle.com/code/ihelon/brain-tumor-eda-with-animations-and-modeling)\n\n# [RSNA STR Pulmonary Embolism Detection](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/194145)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/193401)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/193424)\n\n*Notable mention:* [Fast GPU Experimentation Pipeline](https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection/discussion/193402) by @cdeotte \n\n# [RSNA Intracranial Hemorrhage Detection](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/overview)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/117210)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/116760)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/117223)\n\n*Notable mention:* [A summary post with links to code for each of the gold medal solutions](https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection/discussion/117242) by @rohanrao\n\n# [RSNA Pneumonia Detection Challenge](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/overview)\n\n* [1st place solution](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/discussion/70421)\n* [2nd place solution](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/discussion/70427)\n* [3rd place solution](https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/discussion/70632)\n\n### Other resources you might find useful:\n\n* [πŸ’‘ how to process DICOM images to PNGs](https://www.kaggle.com/code/radek1/how-to-process-dicom-images-to-pngs)\n* [πŸ“Š EDA + training a fast.ai model + submission πŸš€](https://www.kaggle.com/code/radek1/eda-training-a-fast-ai-model-submission)\n* [πŸ€– [fast.ai starter pack] train + inference πŸš€](https://www.kaggle.com/code/radek1/fast-ai-starter-pack-train-inference)\n* [πŸ“Έ Over 56GB of processed data, 5 different methods πŸ₯³](https://www.kaggle.com/competitions/rsna-breast-cancer-detection/discussion/371268)\n* [3 resources to get started with Computer Vision in this competition πŸš€πŸš€πŸš€](https://www.kaggle.com/competitions/rsna-breast-cancer-detection/discussion/369706)\n* [πŸ’‘ 6 Computer Vision tricks for faster training and better models πŸš€πŸš€πŸš€](https://www.kaggle.com/competitions/rsna-breast-cancer-detection/discussion/369155)\n\n\nThank you for reading! Best of luck in the challenge!", "2052425": "first time join, hope we can learn and have some experiment", "2047984": "thanks for sharing !", "2050454": "That is just awesome Radek, such a valuable compilation! Been reading Meta Learning and your newsletter recently, you are really a great inspiration!", "2050203": "Thanks for the resources.", "2048797": "I'm a beginner and this is very helpful, thanks!πŸ˜„", "2339654": "This is really helpful. Thanks for sharing!", "2051538": "", "2134290": "Thank you for sharing this information!" } }