With the PANDA challenge and MICCAI workshop completed, we thought it would be good to give a small update on the current progress. We also hope to address some of the frequently asked questions about the next steps.
\nDataset embargo
\nWe received multiple requests through the Kaggle forum and email whether the data can be used outside of the competition. The short answer is yes, but we kindly ask you not to publish your results until the challenge paper is online.
In more detail: We ask challenge participants / researchers to respect an embargo until the challenge paper has been published. We are currently working with the top-performing teams to write a paper on the challenge, including rigorous analysis of their methods, and it would diminish their efforts if other papers are published in the meantime.
\nAfter the embargo is lifted, participants are free to publish their own results, given that the data use follows the license (CC BY-SA-NC 4.0). So, yes, you can use the dataset for your scientific publications, but only after the challenge paper is published. Currently, this embargo is still in place. That means for now, we kindly ask you to wait before publishing results or submitting to, e.g., arXiv, conferences, or journals. Of course, you are free to post results in this forum or share notebooks on Kaggle as part of continuing the competition. You can also still make late submissions; the embargo only applies to publishing results. Small blog posts on your participation in the challenge are also fine. If you are in doubt, please don't hesitate to ask us!
\nChallenge paper
\nAs described at the start of this competition, the PANDA challenge is part of a larger scientific project for AI-powered prostate cancer grading. As organizers, we are now working on finalizing the PANDA challenge paper, which will describe the results of the competition. From all participating teams, we selected 15 teams that will be part of the PANDA challenge paper. Eight of these teams also presented their work during our MICCAI workshop. We are now working with the selected teams to finalize the paper. The paper will contain more results on the generalization performance of the team on large external datasets. We are quite excited to share this and hope to share more results soon.
When the embargo is lifted and/or the paper has been published, we will update the forum and the PANDA Grand Challenge website.
\nIf there are any questions regarding the paper or the data use, please don't hesitate to reply to this topic or send us an email!
", "messages": [ { "id": 1100687, "postDate": "2020-12-03T08:47:44.070Z", "content": "With the PANDA challenge and MICCAI workshop completed, we thought it would be good to give a small update on the current progress. We also hope to address some of the frequently asked questions about the next steps.
\nDataset embargo
\nWe received multiple requests through the Kaggle forum and email whether the data can be used outside of the competition. The short answer is yes, but we kindly ask you not to publish your results until the challenge paper is online.
In more detail: We ask challenge participants / researchers to respect an embargo until the challenge paper has been published. We are currently working with the top-performing teams to write a paper on the challenge, including rigorous analysis of their methods, and it would diminish their efforts if other papers are published in the meantime.
\nAfter the embargo is lifted, participants are free to publish their own results, given that the data use follows the license (CC BY-SA-NC 4.0). So, yes, you can use the dataset for your scientific publications, but only after the challenge paper is published. Currently, this embargo is still in place. That means for now, we kindly ask you to wait before publishing results or submitting to, e.g., arXiv, conferences, or journals. Of course, you are free to post results in this forum or share notebooks on Kaggle as part of continuing the competition. You can also still make late submissions; the embargo only applies to publishing results. Small blog posts on your participation in the challenge are also fine. If you are in doubt, please don't hesitate to ask us!
\nChallenge paper
\nAs described at the start of this competition, the PANDA challenge is part of a larger scientific project for AI-powered prostate cancer grading. As organizers, we are now working on finalizing the PANDA challenge paper, which will describe the results of the competition. From all participating teams, we selected 15 teams that will be part of the PANDA challenge paper. Eight of these teams also presented their work during our MICCAI workshop. We are now working with the selected teams to finalize the paper. The paper will contain more results on the generalization performance of the team on large external datasets. We are quite excited to share this and hope to share more results soon.
When the embargo is lifted and/or the paper has been published, we will update the forum and the PANDA Grand Challenge website.
\nIf there are any questions regarding the paper or the data use, please don't hesitate to reply to this topic or send us an email!
", "rawMarkdown": "With the PANDA challenge and MICCAI workshop completed, we thought it would be good to give a small update on the current progress. We also hope to address some of the frequently asked questions about the next steps.\n\n**Dataset embargo**\nWe received multiple requests through the Kaggle forum and email whether the data can be used outside of the competition. The short answer is yes, but we kindly ask you not to publish your results until the challenge paper is online.\n\nIn more detail: We ask challenge participants / researchers to respect an embargo until the challenge paper has been published. We are currently working with the top-performing teams to write a paper on the challenge, including rigorous analysis of their methods, and it would diminish their efforts if other papers are published in the meantime.\n\nAfter the embargo is lifted, participants are free to publish their own results, given that the data use follows the license (CC BY-SA-NC 4.0). So, yes, you can use the dataset for your scientific publications, but only after the challenge paper is published. Currently, this embargo is still in place. That means for now, we kindly ask you to wait before publishing results or submitting to, e.g., arXiv, conferences, or journals. Of course, you are free to post results in this forum or share notebooks on Kaggle as part of continuing the competition. You can also still make late submissions; the embargo only applies to publishing results. Small blog posts on your participation in the challenge are also fine. If you are in doubt, please don't hesitate to ask us!\n\n**Challenge paper**\nAs described at the start of this competition, the PANDA challenge is part of a larger scientific project for AI-powered prostate cancer grading. As organizers, we are now working on finalizing the PANDA challenge paper, which will describe the results of the competition. From all participating teams, we selected 15 teams that will be part of the PANDA challenge paper. Eight of these teams also presented their work during our [MICCAI workshop](https://panda.grand-challenge.org/workshop-abstracts/). We are now working with the selected teams to finalize the paper. The paper will contain more results on the generalization performance of the team on large external datasets. We are quite excited to share this and hope to share more results soon.\n\nWhen the embargo is lifted and/or the paper has been published, we will update the forum and the [PANDA Grand Challenge website](https://panda.grand-challenge.org/).\n\nIf there are any questions regarding the paper or the data use, please don't hesitate to reply to this topic or send us an email!\n", "votes": 12 }, { "id": 1643151, "postDate": "2022-01-09T05:42:41.273Z", "content": "@wouterbulten Hello, I saw one MICCAI 2021 paper used this dataset, so I want to ask if I could use the data for MICCAI 2022?
", "rawMarkdown": "@wouterbulten Hello, I saw [one MICCAI 2021 paper](https://doi.org/10.1007/978-3-030-87237-3_32) used this dataset, so I want to ask if I could use the data for MICCAI 2022?", "votes": 1, "replies": [ { "id": 1643520, "postDate": "2022-01-09T13:37:13.477Z", "content": "Hi! We are planning to post an update on the embargo at the end of next week.
", "rawMarkdown": "Hi! We are planning to post an update on the embargo at the end of next week. ", "votes": 2 }, { "id": 1804410, "postDate": "2022-05-28T23:17:02.873Z", "content": "Hello, has the embargo been lifted?
", "rawMarkdown": "Hello, has the embargo been lifted?" }, { "id": 1851427, "postDate": "2022-07-11T08:30:18.087Z", "content": "Yes, please see https://www.kaggle.com/competitions/prostate-cancer-grade-assessment/discussion/300840.
", "rawMarkdown": "Yes, please see https://www.kaggle.com/competitions/prostate-cancer-grade-assessment/discussion/300840." } ] } ], "comments": [ { "id": 1643151, "author_name": "Paceiver", "author_url": "", "post_date": "2022-01-09T05:42:41.273000", "content": "@wouterbulten Hello, I saw one MICCAI 2021 paper used this dataset, so I want to ask if I could use the data for MICCAI 2022?
", "votes": 1, "replies": [ { "id": 1643520, "author_name": "Wouter Bulten", "author_url": "", "post_date": "2022-01-09T13:37:13.477000", "content": "Hi! We are planning to post an update on the embargo at the end of next week.
", "votes": 2, "replies": [] }, { "id": 1804410, "author_name": "alexdconf", "author_url": "", "post_date": "2022-05-28T23:17:02.873000", "content": "Hello, has the embargo been lifted?
", "votes": 0, "replies": [] }, { "id": 1851427, "author_name": "Kimmo Kartasalo", "author_url": "", "post_date": "2022-07-11T08:30:18.087000", "content": "Yes, please see https://www.kaggle.com/competitions/prostate-cancer-grade-assessment/discussion/300840.
", "votes": 0, "replies": [] } ] } ], "raw_markdown_by_id": { "1100687": "With the PANDA challenge and MICCAI workshop completed, we thought it would be good to give a small update on the current progress. We also hope to address some of the frequently asked questions about the next steps.\n\n**Dataset embargo**\nWe received multiple requests through the Kaggle forum and email whether the data can be used outside of the competition. The short answer is yes, but we kindly ask you not to publish your results until the challenge paper is online.\n\nIn more detail: We ask challenge participants / researchers to respect an embargo until the challenge paper has been published. We are currently working with the top-performing teams to write a paper on the challenge, including rigorous analysis of their methods, and it would diminish their efforts if other papers are published in the meantime.\n\nAfter the embargo is lifted, participants are free to publish their own results, given that the data use follows the license (CC BY-SA-NC 4.0). So, yes, you can use the dataset for your scientific publications, but only after the challenge paper is published. Currently, this embargo is still in place. That means for now, we kindly ask you to wait before publishing results or submitting to, e.g., arXiv, conferences, or journals. Of course, you are free to post results in this forum or share notebooks on Kaggle as part of continuing the competition. You can also still make late submissions; the embargo only applies to publishing results. Small blog posts on your participation in the challenge are also fine. If you are in doubt, please don't hesitate to ask us!\n\n**Challenge paper**\nAs described at the start of this competition, the PANDA challenge is part of a larger scientific project for AI-powered prostate cancer grading. As organizers, we are now working on finalizing the PANDA challenge paper, which will describe the results of the competition. From all participating teams, we selected 15 teams that will be part of the PANDA challenge paper. Eight of these teams also presented their work during our [MICCAI workshop](https://panda.grand-challenge.org/workshop-abstracts/). We are now working with the selected teams to finalize the paper. The paper will contain more results on the generalization performance of the team on large external datasets. We are quite excited to share this and hope to share more results soon.\n\nWhen the embargo is lifted and/or the paper has been published, we will update the forum and the [PANDA Grand Challenge website](https://panda.grand-challenge.org/).\n\nIf there are any questions regarding the paper or the data use, please don't hesitate to reply to this topic or send us an email!\n", "1643151": "@wouterbulten Hello, I saw [one MICCAI 2021 paper](https://doi.org/10.1007/978-3-030-87237-3_32) used this dataset, so I want to ask if I could use the data for MICCAI 2022?" } }