{ "id": 266057, "title": "Leaderboard Finalized - Congratulations to the Winners; Recap", "url": "/competitions/siim-covid19-detection/discussion/266057", "author_name": "", "post_date": "2021-08-17T18:35:53.500446400Z", "votes": 23, "comment_count": 1, "views": 0, "content": "

Hey Kagglers,

\n

We’re happy to announce the conclusion of the SIIM-FISABIO-RSNA COVID-19 Detection competition! We’d been working with the folks at SIIM and HP for a long time now to bring a meaningful and exciting competition to the Kaggle community, and we were excited to see it come together!

\n

This year’s competition ended with 1,786 participants on 1,305 teams! We had 32,307 submissions from 83 countries! For 337 users (including 20 users on top 100 teams!), this was their first competition. We also had 5 new Grandmasters and 16 new Masters at the conclusion of the competition! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!

\n

As said before, we were once again very pleased to work with the team at SIIM (Anna and Dr. Lakhani, RSNA Chris and at HP Andrew. We're glad they chose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future.

\n

We're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.

\n

We've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.

\n

The top potential winning teams have been contacted via email to provide their winning solutions for host review, which is underway. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams. The winners of the student prize have also been contacted for verification as well.

\n

You should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.

\n

In the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top notebooks, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.

\n

Happy Modeling!
\nKaggle Team

\n

Top Solution Write-ups

\n\n

Top Notebooks

\n\n

Other Top Discussions

\n", "messages": [ { "id": "1478017", "postDate": "08/17/2021 18:35:53", "content": "

Hey Kagglers,

\n

We’re happy to announce the conclusion of the SIIM-FISABIO-RSNA COVID-19 Detection competition! We’d been working with the folks at SIIM and HP for a long time now to bring a meaningful and exciting competition to the Kaggle community, and we were excited to see it come together!

\n

This year’s competition ended with 1,786 participants on 1,305 teams! We had 32,307 submissions from 83 countries! For 337 users (including 20 users on top 100 teams!), this was their first competition. We also had 5 new Grandmasters and 16 new Masters at the conclusion of the competition! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!

\n

As said before, we were once again very pleased to work with the team at SIIM (Anna and Dr. Lakhani, RSNA Chris and at HP Andrew. We're glad they chose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future.

\n

We're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.

\n

We've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.

\n

The top potential winning teams have been contacted via email to provide their winning solutions for host review, which is underway. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams. The winners of the student prize have also been contacted for verification as well.

\n

You should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.

\n

In the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top notebooks, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.

\n

Happy Modeling!
\nKaggle Team

\n

Top Solution Write-ups

\n\n

Top Notebooks

\n\n

Other Top Discussions

\n", "rawMarkdown": "Hey Kagglers,\n\nWe’re happy to announce the conclusion of the SIIM-FISABIO-RSNA COVID-19 Detection competition! We’d been working with the folks at SIIM and HP for a long time now to bring a meaningful and exciting competition to the Kaggle community, and we were excited to see it come together!\n\nThis year’s competition ended with 1,786 participants on 1,305 teams! We had 32,307 submissions from 83 countries! For 337 users (including 20 users on top 100 teams!), this was their first competition. We also had 5 new Grandmasters and 16 new Masters at the conclusion of the competition! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking! \n\nAs said before, we were once again very pleased to work with the team at SIIM ([Anna](https://www.kaggle.com/annazawacki) and [Dr. Lakhani](https://www.kaggle.com/ParasLakhani), RSNA [Chris](https://www.kaggle.com/cdcarr) and at HP [Andrew](https://www.kaggle.com/andrewkemp). We're glad they chose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future. \n\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.\n\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact [compliance](https://www.kaggle.com/compliance). Please fill in all the fields honestly.\n\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review, which is underway. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams. The winners of the student prize have also been contacted for verification as well.\n\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.\n\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top notebooks, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.\n\nHappy Modeling!\nKaggle Team\n\n###Top Solution Write-ups\n\n- [1st Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263658)\n- [2nd Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263674)\n- [3rd Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263654)\n- [4th Place a](https://www.kaggle.com/c/siim-covid19-detection/discussion/263676)\n- [4th Place b](https://www.kaggle.com/c/siim-covid19-detection/discussion/264243)\n- [5th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263945)\n- [6th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/264858)\n- [7th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263748)\n- [8th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263734)\n- [9th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/265583)\n- [10th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263683)\n- [11th Place a](https://www.kaggle.com/c/siim-covid19-detection/discussion/263701)\n- [11th Place b](https://www.kaggle.com/c/siim-covid19-detection/discussion/264287)\n- [12th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/264311)\n- [19th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263662)\n- [24th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263895)\n- [27th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/264028)\n- [32nd Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263849)\n- [47th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263830)\n\n###Top Notebooks\n- [Pulmonary Dicom Preprocessing](https://www.kaggle.com/allunia/pulmonary-dicom-preprocessing)\n- [😷SIIM Covid-19: Box Detect & .dcm metadata](https://www.kaggle.com/andradaolteanu/siim-covid-19-box-detect-dcm-metadata)\n- [[Train] COVID-19 Detection using YOLOv5](https://www.kaggle.com/ayuraj/train-covid-19-detection-using-yolov5)\n- [SIIM COVID-19 Detection: EDA + Data Augmentation](https://www.kaggle.com/ruchi798/siim-covid-19-detection-eda-data-augmentation)\n- [SIIM COVID-19 Detection - a simple EDA 🦠🩺](https://www.kaggle.com/tanlikesmath/siim-covid-19-detection-a-simple-eda)\n- [siim-cov19 efnb7+yolov5 [infer]](https://www.kaggle.com/h053473666/siim-cov19-efnb7-yolov5-infer)\n\n###Other Top Discussions\n- [Recap top solutions for Xray Medical Imaging comps](https://www.kaggle.com/c/siim-covid19-detection/discussion/239891)\n- [[placeholder] lb 0.450 (study only) starter kit!](https://www.kaggle.com/c/siim-covid19-detection/discussion/240233)\n- [Understanding Studies](https://www.kaggle.com/c/siim-covid19-detection/discussion/2408788)\n- [Understand the Competition Better - Demystifying Submission Details](https://www.kaggle.com/c/siim-covid19-detection/discussion/240329)\n- [Resized images in JPG/PNG and different sizes](https://www.kaggle.com/c/siim-covid19-detection/discussion/239918)\n- [External data - 1000 triple-read Covid-19 X-rays](https://www.kaggle.com/c/siim-covid19-detection/discussion/240187)", "votes": null }, { "id": "1482203", "postDate": "08/20/2021 00:13:18", "content": "

congrats to winners

", "rawMarkdown": "congrats to winners", "votes": null } ], "comments": [ { "id": 1482203, "author_name": "safa2masoud", "author_url": "", "post_date": "08/20/2021 00:13:18", "content": "

congrats to winners

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1478017": "Hey Kagglers,\n\nWe’re happy to announce the conclusion of the SIIM-FISABIO-RSNA COVID-19 Detection competition! We’d been working with the folks at SIIM and HP for a long time now to bring a meaningful and exciting competition to the Kaggle community, and we were excited to see it come together!\n\nThis year’s competition ended with 1,786 participants on 1,305 teams! We had 32,307 submissions from 83 countries! For 337 users (including 20 users on top 100 teams!), this was their first competition. We also had 5 new Grandmasters and 16 new Masters at the conclusion of the competition! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking! \n\nAs said before, we were once again very pleased to work with the team at SIIM ([Anna](https://www.kaggle.com/annazawacki) and [Dr. Lakhani](https://www.kaggle.com/ParasLakhani), RSNA [Chris](https://www.kaggle.com/cdcarr) and at HP [Andrew](https://www.kaggle.com/andrewkemp). We're glad they chose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future. \n\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.\n\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact [compliance](https://www.kaggle.com/compliance). Please fill in all the fields honestly.\n\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review, which is underway. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams. The winners of the student prize have also been contacted for verification as well.\n\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.\n\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top notebooks, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.\n\nHappy Modeling!\nKaggle Team\n\n###Top Solution Write-ups\n\n- [1st Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263658)\n- [2nd Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263674)\n- [3rd Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263654)\n- [4th Place a](https://www.kaggle.com/c/siim-covid19-detection/discussion/263676)\n- [4th Place b](https://www.kaggle.com/c/siim-covid19-detection/discussion/264243)\n- [5th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263945)\n- [6th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/264858)\n- [7th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263748)\n- [8th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263734)\n- [9th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/265583)\n- [10th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263683)\n- [11th Place a](https://www.kaggle.com/c/siim-covid19-detection/discussion/263701)\n- [11th Place b](https://www.kaggle.com/c/siim-covid19-detection/discussion/264287)\n- [12th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/264311)\n- [19th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263662)\n- [24th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263895)\n- [27th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/264028)\n- [32nd Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263849)\n- [47th Place](https://www.kaggle.com/c/siim-covid19-detection/discussion/263830)\n\n###Top Notebooks\n- [Pulmonary Dicom Preprocessing](https://www.kaggle.com/allunia/pulmonary-dicom-preprocessing)\n- [😷SIIM Covid-19: Box Detect & .dcm metadata](https://www.kaggle.com/andradaolteanu/siim-covid-19-box-detect-dcm-metadata)\n- [[Train] COVID-19 Detection using YOLOv5](https://www.kaggle.com/ayuraj/train-covid-19-detection-using-yolov5)\n- [SIIM COVID-19 Detection: EDA + Data Augmentation](https://www.kaggle.com/ruchi798/siim-covid-19-detection-eda-data-augmentation)\n- [SIIM COVID-19 Detection - a simple EDA 🦠🩺](https://www.kaggle.com/tanlikesmath/siim-covid-19-detection-a-simple-eda)\n- [siim-cov19 efnb7+yolov5 [infer]](https://www.kaggle.com/h053473666/siim-cov19-efnb7-yolov5-infer)\n\n###Other Top Discussions\n- [Recap top solutions for Xray Medical Imaging comps](https://www.kaggle.com/c/siim-covid19-detection/discussion/239891)\n- [[placeholder] lb 0.450 (study only) starter kit!](https://www.kaggle.com/c/siim-covid19-detection/discussion/240233)\n- [Understanding Studies](https://www.kaggle.com/c/siim-covid19-detection/discussion/2408788)\n- [Understand the Competition Better - Demystifying Submission Details](https://www.kaggle.com/c/siim-covid19-detection/discussion/240329)\n- [Resized images in JPG/PNG and different sizes](https://www.kaggle.com/c/siim-covid19-detection/discussion/239918)\n- [External data - 1000 triple-read Covid-19 X-rays](https://www.kaggle.com/c/siim-covid19-detection/discussion/240187)", "1482203": "congrats to winners" }, "source": "meta" }