{
  "id": 461669,
  "title": "Seeking Insights and Experiences Until Now",
  "url": "/competitions/UBC-OCEAN/discussion/461669",
  "author_name": "Mohammad Dehghanmanshadi",
  "post_date": "2023-12-15T18:23:38.078000",
  "votes": 2,
  "comment_count": 1,
  "views": 0,
  "content": "<p>I hope you're all doing well! 👋 I would love to hear about your experiences and insights. Let's share our learnings and strategies to benefit everyone in the community.</p>\n<p><strong>Questions to Start:</strong></p>\n<ol>\n<li>How are you approaching the classification?</li>\n<li>Any insights on handling the two categories of images - whole slide images (WSI) and tissue microarray (TMA) - and their different characteristics?</li>\n<li>Thoughts on the challenge of identifying outliers, especially with the \"Other\" class not present in the training set?</li>\n<li>What considerations are you making for the expansive test set, including differences in image dimensions, quality, slide staining techniques, and more?</li>\n</ol>\n<p>Feel free to share code snippets or any lessons learned from your experimentation. </p>\n<p><strong>Happy coding!</strong> 🚀</p>",
  "messages": [
    {
      "id": 2563154,
      "postDate": "2023-12-16T04:21:36.693Z",
      "content": "<p>would love to hear you and others thoughts on all the topics! </p>\n<p>I can start with mine: I just found that TMAs have thumbnails in the test data and around 9/16 are TMAs! </p>",
      "rawMarkdown": "would love to hear you and others thoughts on all the topics! \n\nI can start with mine: I just found that TMAs have thumbnails in the test data and around 9/16 are TMAs! ",
      "votes": 3
    },
    {
      "id": 2562884,
      "postDate": "2023-12-15T18:23:38.080Z",
      "content": "<p>I hope you're all doing well! 👋 I would love to hear about your experiences and insights. Let's share our learnings and strategies to benefit everyone in the community.</p>\n<p><strong>Questions to Start:</strong></p>\n<ol>\n<li>How are you approaching the classification?</li>\n<li>Any insights on handling the two categories of images - whole slide images (WSI) and tissue microarray (TMA) - and their different characteristics?</li>\n<li>Thoughts on the challenge of identifying outliers, especially with the \"Other\" class not present in the training set?</li>\n<li>What considerations are you making for the expansive test set, including differences in image dimensions, quality, slide staining techniques, and more?</li>\n</ol>\n<p>Feel free to share code snippets or any lessons learned from your experimentation. </p>\n<p><strong>Happy coding!</strong> 🚀</p>",
      "rawMarkdown": "I hope you're all doing well! 👋 I would love to hear about your experiences and insights. Let's share our learnings and strategies to benefit everyone in the community.\n\n**Questions to Start:**\n\n1. How are you approaching the classification?\n2. Any insights on handling the two categories of images - whole slide images (WSI) and tissue microarray (TMA) - and their different characteristics?\n3. Thoughts on the challenge of identifying outliers, especially with the \"Other\" class not present in the training set?\n4. What considerations are you making for the expansive test set, including differences in image dimensions, quality, slide staining techniques, and more?\n\nFeel free to share code snippets or any lessons learned from your experimentation. \n\n**Happy coding!** 🚀",
      "votes": 2
    }
  ],
  "comments": [
    {
      "id": 2563154,
      "author_name": "Yoobin",
      "author_url": "",
      "post_date": "2023-12-16T04:21:36.693000",
      "content": "<p>would love to hear you and others thoughts on all the topics! </p>\n<p>I can start with mine: I just found that TMAs have thumbnails in the test data and around 9/16 are TMAs! </p>",
      "votes": 3,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2563154": "would love to hear you and others thoughts on all the topics! \n\nI can start with mine: I just found that TMAs have thumbnails in the test data and around 9/16 are TMAs! ",
    "2562884": "I hope you're all doing well! 👋 I would love to hear about your experiences and insights. Let's share our learnings and strategies to benefit everyone in the community.\n\n**Questions to Start:**\n\n1. How are you approaching the classification?\n2. Any insights on handling the two categories of images - whole slide images (WSI) and tissue microarray (TMA) - and their different characteristics?\n3. Thoughts on the challenge of identifying outliers, especially with the \"Other\" class not present in the training set?\n4. What considerations are you making for the expansive test set, including differences in image dimensions, quality, slide staining techniques, and more?\n\nFeel free to share code snippets or any lessons learned from your experimentation. \n\n**Happy coding!** 🚀"
  }
}