{
  "id": 187927,
  "title": "Educational Merit Distinction",
  "url": "/competitions/rsna-str-pulmonary-embolism-detection/discussion/187927",
  "author_name": "John Mongan",
  "post_date": "2020-09-30T23:38:51.603000",
  "votes": 11,
  "comment_count": 0,
  "views": 0,
  "content": "<p>The competition hosts are pleased to announce an additional aspect of this year's challenge: The Educational Merit Distinction.</p>\n<p>The top ten placing entrants on the private leader board at the close of the competition will be reviewed by a panel of judges for the purpose of awarding an Educational Merit distinction. Judges will evaluate the training code, inference code and any associated documentation and supporting materials, including any live websites or hosted demonstrations of the algorithm.</p>\n<p>Judges will be looking for:</p>\n<ul>\n<li>clarity and comprehensiveness of the explanation of the approach taken by the entrant</li>\n<li>clarity, accessibility, organization and architecture of the code</li>\n<li>estimated effort required to run the code (e.g. reproduce results by retraining, run inference on a new set of data)</li>\n<li>ease of re-use and re-purposing of code</li>\n<li>novelty of approach</li>\n</ul>\n<p>Entrants awarded the Educational Merit distinction will be invited to submit an article describing their work to <a href=\"https://pubs.rsna.org/journal/ai\" target=\"_blank\"><em>Radiology: Artificial Intelligence</em></a>. If, in the judges’ sole opinion, there are multiple entrants with equally exceptional merit, more than one distinction may be awarded. This distinction is judged and administered solely by the hosts and does not involve kaggle. Only the top 10 placing entrants (on the private leaderboard) at the close of the competition are eligible for this distinction. There is no additional monetary prize associated with this distinction.</p>",
  "messages": [
    {
      "id": 1033381,
      "postDate": "2020-09-30T23:38:51.603Z",
      "content": "<p>The competition hosts are pleased to announce an additional aspect of this year's challenge: The Educational Merit Distinction.</p>\n<p>The top ten placing entrants on the private leader board at the close of the competition will be reviewed by a panel of judges for the purpose of awarding an Educational Merit distinction. Judges will evaluate the training code, inference code and any associated documentation and supporting materials, including any live websites or hosted demonstrations of the algorithm.</p>\n<p>Judges will be looking for:</p>\n<ul>\n<li>clarity and comprehensiveness of the explanation of the approach taken by the entrant</li>\n<li>clarity, accessibility, organization and architecture of the code</li>\n<li>estimated effort required to run the code (e.g. reproduce results by retraining, run inference on a new set of data)</li>\n<li>ease of re-use and re-purposing of code</li>\n<li>novelty of approach</li>\n</ul>\n<p>Entrants awarded the Educational Merit distinction will be invited to submit an article describing their work to <a href=\"https://pubs.rsna.org/journal/ai\" target=\"_blank\"><em>Radiology: Artificial Intelligence</em></a>. If, in the judges’ sole opinion, there are multiple entrants with equally exceptional merit, more than one distinction may be awarded. This distinction is judged and administered solely by the hosts and does not involve kaggle. Only the top 10 placing entrants (on the private leaderboard) at the close of the competition are eligible for this distinction. There is no additional monetary prize associated with this distinction.</p>",
      "rawMarkdown": "The competition hosts are pleased to announce an additional aspect of this year's challenge: The Educational Merit Distinction.\n\nThe top ten placing entrants on the private leader board at the close of the competition will be reviewed by a panel of judges for the purpose of awarding an Educational Merit distinction. Judges will evaluate the training code, inference code and any associated documentation and supporting materials, including any live websites or hosted demonstrations of the algorithm.\n \nJudges will be looking for:\n- clarity and comprehensiveness of the explanation of the approach taken by the entrant\n- clarity, accessibility, organization and architecture of the code\n- estimated effort required to run the code (e.g. reproduce results by retraining, run inference on a new set of data)\n- ease of re-use and re-purposing of code\n- novelty of approach\n\nEntrants awarded the Educational Merit distinction will be invited to submit an article describing their work to [*Radiology: Artificial Intelligence*](https://pubs.rsna.org/journal/ai). If, in the judges’ sole opinion, there are multiple entrants with equally exceptional merit, more than one distinction may be awarded. This distinction is judged and administered solely by the hosts and does not involve kaggle. Only the top 10 placing entrants (on the private leaderboard) at the close of the competition are eligible for this distinction. There is no additional monetary prize associated with this distinction.\n",
      "votes": 11
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "1033381": "The competition hosts are pleased to announce an additional aspect of this year's challenge: The Educational Merit Distinction.\n\nThe top ten placing entrants on the private leader board at the close of the competition will be reviewed by a panel of judges for the purpose of awarding an Educational Merit distinction. Judges will evaluate the training code, inference code and any associated documentation and supporting materials, including any live websites or hosted demonstrations of the algorithm.\n \nJudges will be looking for:\n- clarity and comprehensiveness of the explanation of the approach taken by the entrant\n- clarity, accessibility, organization and architecture of the code\n- estimated effort required to run the code (e.g. reproduce results by retraining, run inference on a new set of data)\n- ease of re-use and re-purposing of code\n- novelty of approach\n\nEntrants awarded the Educational Merit distinction will be invited to submit an article describing their work to [*Radiology: Artificial Intelligence*](https://pubs.rsna.org/journal/ai). If, in the judges’ sole opinion, there are multiple entrants with equally exceptional merit, more than one distinction may be awarded. This distinction is judged and administered solely by the hosts and does not involve kaggle. Only the top 10 placing entrants (on the private leaderboard) at the close of the competition are eligible for this distinction. There is no additional monetary prize associated with this distinction.\n"
  }
}