{
  "id": 207817,
  "title": "Some Genders missing from DICOM data?",
  "url": "/competitions/vinbigdata-chest-xray-abnormalities-detection/discussion/207817",
  "author_name": "Yerram Varun",
  "post_date": "2020-12-31T11:32:12.382000",
  "votes": 3,
  "comment_count": 2,
  "views": 0,
  "content": "<p>This is the DICOM Data for the id 21a10246a5ec7af151081d0cd6d65dc9<br>\n<img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Ff8dd8620ee7b297f73954774f1d21233%2FScreenshot%20from%202020-12-31%2016-38-30.png?generation=1609413989311232&amp;alt=media\" alt=\"\"></p>\n<p>As we can see the PatientSex Attribute is empty.<br>\nAlso,<br>\n<img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Fb82e5f7294c191a8a020810c6b23baa7%2FScreenshot%20from%202020-12-31%2016-56-56.png?generation=1609414038899771&amp;alt=media\" alt=\"\"><br>\nHence a significant number of Sex Attributes are empty.</p>\n<p>Does it mean we have to only use Images for the classification or is there an imputation strategy?</p>",
  "messages": [
    {
      "id": 1133615,
      "postDate": "2020-12-31T11:32:12.383Z",
      "content": "<p>This is the DICOM Data for the id 21a10246a5ec7af151081d0cd6d65dc9<br>\n<img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Ff8dd8620ee7b297f73954774f1d21233%2FScreenshot%20from%202020-12-31%2016-38-30.png?generation=1609413989311232&amp;alt=media\" alt=\"\"></p>\n<p>As we can see the PatientSex Attribute is empty.<br>\nAlso,<br>\n<img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Fb82e5f7294c191a8a020810c6b23baa7%2FScreenshot%20from%202020-12-31%2016-56-56.png?generation=1609414038899771&amp;alt=media\" alt=\"\"><br>\nHence a significant number of Sex Attributes are empty.</p>\n<p>Does it mean we have to only use Images for the classification or is there an imputation strategy?</p>",
      "rawMarkdown": "This is the DICOM Data for the id 21a10246a5ec7af151081d0cd6d65dc9\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Ff8dd8620ee7b297f73954774f1d21233%2FScreenshot%20from%202020-12-31%2016-38-30.png?generation=1609413989311232&alt=media)\n\nAs we can see the PatientSex Attribute is empty.\nAlso,\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Fb82e5f7294c191a8a020810c6b23baa7%2FScreenshot%20from%202020-12-31%2016-56-56.png?generation=1609414038899771&alt=media)\nHence a significant number of Sex Attributes are empty.\n\nDoes it mean we have to only use Images for the classification or is there an imputation strategy?\n",
      "votes": 3
    },
    {
      "id": 1133762,
      "postDate": "2020-12-31T14:03:07.640Z",
      "content": "<p>I just found out that gender data is available. Thank you for the valuable information.<br>\nAs for the gender, it may be possible to determine it from the size of the soft tissue in the chest since it is a chest radiograph, so it might be possible to complement it.</p>",
      "rawMarkdown": "I just found out that gender data is available. Thank you for the valuable information.\nAs for the gender, it may be possible to determine it from the size of the soft tissue in the chest since it is a chest radiograph, so it might be possible to complement it.",
      "replies": [
        {
          "id": 1133806,
          "postDate": "2020-12-31T14:43:30.460Z",
          "content": "<p>Hey, thanks for the insight! The model then should be capable of learning gender on its own.</p>",
          "rawMarkdown": "Hey, thanks for the insight! The model then should be capable of learning gender on its own."
        }
      ]
    }
  ],
  "comments": [
    {
      "id": 1133762,
      "author_name": "ANZ",
      "author_url": "",
      "post_date": "2020-12-31T14:03:07.640000",
      "content": "<p>I just found out that gender data is available. Thank you for the valuable information.<br>\nAs for the gender, it may be possible to determine it from the size of the soft tissue in the chest since it is a chest radiograph, so it might be possible to complement it.</p>",
      "votes": 0,
      "replies": [
        {
          "id": 1133806,
          "author_name": "Yerram Varun",
          "author_url": "",
          "post_date": "2020-12-31T14:43:30.460000",
          "content": "<p>Hey, thanks for the insight! The model then should be capable of learning gender on its own.</p>",
          "votes": 0,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "1133615": "This is the DICOM Data for the id 21a10246a5ec7af151081d0cd6d65dc9\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Ff8dd8620ee7b297f73954774f1d21233%2FScreenshot%20from%202020-12-31%2016-38-30.png?generation=1609413989311232&alt=media)\n\nAs we can see the PatientSex Attribute is empty.\nAlso,\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F4630396%2Fb82e5f7294c191a8a020810c6b23baa7%2FScreenshot%20from%202020-12-31%2016-56-56.png?generation=1609414038899771&alt=media)\nHence a significant number of Sex Attributes are empty.\n\nDoes it mean we have to only use Images for the classification or is there an imputation strategy?\n",
    "1133762": "I just found out that gender data is available. Thank you for the valuable information.\nAs for the gender, it may be possible to determine it from the size of the soft tissue in the chest since it is a chest radiograph, so it might be possible to complement it."
  }
}