{
  "id": 253181,
  "title": "Challenge Problem",
  "url": "/competitions/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/253181",
  "author_name": "",
  "post_date": "2021-07-15T09:04:59.640823300Z",
  "votes": 1,
  "comment_count": 4,
  "views": 0,
  "content": "<p>Hi,<br>\nI wanted to know is this Image classification challenge?</p>",
  "messages": [
    {
      "id": "1388848",
      "postDate": "07/15/2021 09:04:59",
      "content": "<p>Hi,<br>\nI wanted to know is this Image classification challenge?</p>",
      "rawMarkdown": "Hi,\nI wanted to know is this Image classification challenge?",
      "votes": null
    },
    {
      "id": "1390460",
      "postDate": "07/16/2021 17:01:50",
      "content": "<p>Hi,</p>\n<p>it is a binary classification problem at patient level. </p>\n<p>Evrey patient has subfolder </p>\n<ul>\n<li>Flair</li>\n<li>T1w</li>\n<li>T1wCE</li>\n<li>T2w</li>\n</ul>\n<p>with images. Out of that you have to build a model that process this images and returns an prediction you likely that patient has tumor.</p>\n<p>I made a very basic inference notebook. So you may get an idea of the problem to solve.</p>\n<p><a href=\"https://www.kaggle.com/lucamtb/brain-tumor-very-basice-inference\" target=\"_blank\">https://www.kaggle.com/lucamtb/brain-tumor-very-basice-inference</a></p>",
      "rawMarkdown": "Hi,\n\nit is a binary classification problem at patient level. \n\nEvrey patient has subfolder \n\n- Flair\n- T1w\n- T1wCE\n- T2w\n\nwith images. Out of that you have to build a model that process this images and returns an prediction you likely that patient has tumor.\n\nI made a very basic inference notebook. So you may get an idea of the problem to solve.\n\nhttps://www.kaggle.com/lucamtb/brain-tumor-very-basice-inference",
      "votes": null
    },
    {
      "id": "1391561",
      "postDate": "07/17/2021 17:54:19",
      "content": "<p>Great reply! Thank you for sharing your notebook link!</p>",
      "rawMarkdown": "Great reply! Thank you for sharing your notebook link!",
      "votes": null
    },
    {
      "id": "1391564",
      "postDate": "07/17/2021 17:57:22",
      "content": "<p>Here is are some additional helpful discussions you may want to take a look at, as well:</p>\n<ul>\n<li><a href=\"https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252972\" target=\"_blank\">data itself discussion</a></li>\n<li><a href=\"https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252844\" target=\"_blank\">why it's called a radiogenomic classification</a></li>\n<li><a href=\"https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252886\" target=\"_blank\">AUC-ROC curve</a></li>\n</ul>",
      "rawMarkdown": "Here is are some additional helpful discussions you may want to take a look at, as well:\n- [data itself discussion](https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252972)\n- [why it's called a radiogenomic classification](https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252844)\n- [AUC-ROC curve](https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252886)",
      "votes": null
    },
    {
      "id": "1392817",
      "postDate": "07/19/2021 05:34:05",
      "content": "<p>Are are welcome. If you like the notebook or find It usefull you can upvote It. 😃</p>",
      "rawMarkdown": "Are are welcome. If you like the notebook or find It usefull you can upvote It. 😃",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1390460,
      "author_name": "lucamtb",
      "author_url": "",
      "post_date": "07/16/2021 17:01:50",
      "content": "<p>Hi,</p>\n<p>it is a binary classification problem at patient level. </p>\n<p>Evrey patient has subfolder </p>\n<ul>\n<li>Flair</li>\n<li>T1w</li>\n<li>T1wCE</li>\n<li>T2w</li>\n</ul>\n<p>with images. Out of that you have to build a model that process this images and returns an prediction you likely that patient has tumor.</p>\n<p>I made a very basic inference notebook. So you may get an idea of the problem to solve.</p>\n<p><a href=\"https://www.kaggle.com/lucamtb/brain-tumor-very-basice-inference\" target=\"_blank\">https://www.kaggle.com/lucamtb/brain-tumor-very-basice-inference</a></p>",
      "votes": null,
      "replies": [
        {
          "id": 1391561,
          "author_name": "elenaeb",
          "author_url": "",
          "post_date": "07/17/2021 17:54:19",
          "content": "<p>Great reply! Thank you for sharing your notebook link!</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 1392817,
          "author_name": "lucamtb",
          "author_url": "",
          "post_date": "07/19/2021 05:34:05",
          "content": "<p>Are are welcome. If you like the notebook or find It usefull you can upvote It. 😃</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 1391564,
      "author_name": "elenaeb",
      "author_url": "",
      "post_date": "07/17/2021 17:57:22",
      "content": "<p>Here is are some additional helpful discussions you may want to take a look at, as well:</p>\n<ul>\n<li><a href=\"https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252972\" target=\"_blank\">data itself discussion</a></li>\n<li><a href=\"https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252844\" target=\"_blank\">why it's called a radiogenomic classification</a></li>\n<li><a href=\"https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252886\" target=\"_blank\">AUC-ROC curve</a></li>\n</ul>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1388848": "Hi,\nI wanted to know is this Image classification challenge?",
    "1390460": "Hi,\n\nit is a binary classification problem at patient level. \n\nEvrey patient has subfolder \n\n- Flair\n- T1w\n- T1wCE\n- T2w\n\nwith images. Out of that you have to build a model that process this images and returns an prediction you likely that patient has tumor.\n\nI made a very basic inference notebook. So you may get an idea of the problem to solve.\n\nhttps://www.kaggle.com/lucamtb/brain-tumor-very-basice-inference",
    "1391561": "Great reply! Thank you for sharing your notebook link!",
    "1391564": "Here is are some additional helpful discussions you may want to take a look at, as well:\n- [data itself discussion](https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252972)\n- [why it's called a radiogenomic classification](https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252844)\n- [AUC-ROC curve](https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/discussion/252886)",
    "1392817": "Are are welcome. If you like the notebook or find It usefull you can upvote It. 😃"
  },
  "source": "meta"
}