{
  "id": 445680,
  "title": "No region information of the lesion. No normal image.",
  "url": "/competitions/UBC-OCEAN/discussion/445680",
  "author_name": "stpete_ishii",
  "post_date": "2023-10-08T09:53:57.608000",
  "votes": 4,
  "comment_count": 1,
  "views": 0,
  "content": "<p>To solve this problem, the model needs to learn the tissue structure of the lesion site. However, the training data does not provide region information (polygon/rectangle/raster) of the lesion site. Further, there are no images of normal tissue. I can list the pathological features of each finding, but expect the model to find an independent identification method.</p>",
  "messages": [
    {
      "id": 2474141,
      "postDate": "2023-10-09T02:14:03.017Z",
      "content": "<p>List of characteristics of findings.</p>\n<table>\n<thead>\n<tr>\n<th>Finding</th>\n<th>Tumor Nature</th>\n<th>Tumor Shape</th>\n<th>Tumor Surroundings</th>\n<th>Tumor Vasculature</th>\n<th>Tumor Cells</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td>HGSC</td>\n<td>Malignant epithelial tumor</td>\n<td>Multilocular</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>LGSC</td>\n<td>Low-malignant epithelial tumor</td>\n<td>Uniloculated</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>EC</td>\n<td>Germ cell tumor</td>\n<td>Variable</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>CC</td>\n<td>Sex cord-stromal tumor</td>\n<td>Variable</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>MC</td>\n<td>Ovarian chocolate cyst</td>\n<td>Benign</td>\n<td>Uniloculated</td>\n<td>Scant</td>\n<td>Few atypical cells</td>\n</tr>\n</tbody>\n</table>\n<p>Bard taught me. </p>",
      "rawMarkdown": "List of characteristics of findings.\n\n| Finding | Tumor Nature | Tumor Shape | Tumor Surroundings | Tumor Vasculature | Tumor Cells |\n|---|---|---|---|---|---|\n| HGSC | Malignant epithelial tumor | Multilocular | Inflammation and adhesion | Abundant | Atypical cells |\n| LGSC | Low-malignant epithelial tumor | Uniloculated | Inflammation and adhesion | Abundant | Atypical cells |\n| EC | Germ cell tumor | Variable | Inflammation and adhesion | Abundant | Atypical cells |\n| CC | Sex cord-stromal tumor | Variable | Inflammation and adhesion | Abundant | Atypical cells |\n| MC | Ovarian chocolate cyst | Benign | Uniloculated | Scant | Few atypical cells |\n\nBard taught me. \n",
      "votes": 4
    },
    {
      "id": 2473471,
      "postDate": "2023-10-08T09:53:57.610Z",
      "content": "<p>To solve this problem, the model needs to learn the tissue structure of the lesion site. However, the training data does not provide region information (polygon/rectangle/raster) of the lesion site. Further, there are no images of normal tissue. I can list the pathological features of each finding, but expect the model to find an independent identification method.</p>",
      "rawMarkdown": "To solve this problem, the model needs to learn the tissue structure of the lesion site. However, the training data does not provide region information (polygon/rectangle/raster) of the lesion site. Further, there are no images of normal tissue. I can list the pathological features of each finding, but expect the model to find an independent identification method.",
      "votes": 4
    }
  ],
  "comments": [
    {
      "id": 2474141,
      "author_name": "stpete_ishii",
      "author_url": "",
      "post_date": "2023-10-09T02:14:03.017000",
      "content": "<p>List of characteristics of findings.</p>\n<table>\n<thead>\n<tr>\n<th>Finding</th>\n<th>Tumor Nature</th>\n<th>Tumor Shape</th>\n<th>Tumor Surroundings</th>\n<th>Tumor Vasculature</th>\n<th>Tumor Cells</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td>HGSC</td>\n<td>Malignant epithelial tumor</td>\n<td>Multilocular</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>LGSC</td>\n<td>Low-malignant epithelial tumor</td>\n<td>Uniloculated</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>EC</td>\n<td>Germ cell tumor</td>\n<td>Variable</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>CC</td>\n<td>Sex cord-stromal tumor</td>\n<td>Variable</td>\n<td>Inflammation and adhesion</td>\n<td>Abundant</td>\n<td>Atypical cells</td>\n</tr>\n<tr>\n<td>MC</td>\n<td>Ovarian chocolate cyst</td>\n<td>Benign</td>\n<td>Uniloculated</td>\n<td>Scant</td>\n<td>Few atypical cells</td>\n</tr>\n</tbody>\n</table>\n<p>Bard taught me. </p>",
      "votes": 4,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2474141": "List of characteristics of findings.\n\n| Finding | Tumor Nature | Tumor Shape | Tumor Surroundings | Tumor Vasculature | Tumor Cells |\n|---|---|---|---|---|---|\n| HGSC | Malignant epithelial tumor | Multilocular | Inflammation and adhesion | Abundant | Atypical cells |\n| LGSC | Low-malignant epithelial tumor | Uniloculated | Inflammation and adhesion | Abundant | Atypical cells |\n| EC | Germ cell tumor | Variable | Inflammation and adhesion | Abundant | Atypical cells |\n| CC | Sex cord-stromal tumor | Variable | Inflammation and adhesion | Abundant | Atypical cells |\n| MC | Ovarian chocolate cyst | Benign | Uniloculated | Scant | Few atypical cells |\n\nBard taught me. \n",
    "2473471": "To solve this problem, the model needs to learn the tissue structure of the lesion site. However, the training data does not provide region information (polygon/rectangle/raster) of the lesion site. Further, there are no images of normal tissue. I can list the pathological features of each finding, but expect the model to find an independent identification method."
  }
}