{
  "id": 65440,
  "title": "a group of experienced radiologists with diagnosing the presence of pneumonia ",
  "url": "/competitions/rsna-pneumonia-detection-challenge/discussion/65440",
  "author_name": "",
  "post_date": "2018-09-11T00:15:26.432922800Z",
  "votes": 4,
  "comment_count": 1,
  "views": 0,
  "content": "<p><a href=\"https://unanimous.ai/stanford-radiology/\">https://unanimous.ai/stanford-radiology/</a></p>\n\n<p>I apologize if someone posted this already.</p>\n\n<p>...As presented at the 2018 SIIM Conference on Machine Intelligence in Medical Imaging, the study tasked a group of experienced radiologists with diagnosing the presence of pneumonia in chest X-rays. This is one of the most widely performed imaging procedures in the US, with more than 1 million adults hospitalized with pneumonia each year. But, despite this prevalence, accurately diagnosing X-rays is highly challenging with significant variability across radiologists. This makes it both an optimal task for applying new AI technologies, and an important problem to solve for the medical community....</p>",
  "messages": [
    {
      "id": "385405",
      "postDate": "09/11/2018 00:15:26",
      "content": "<p><a href=\"https://unanimous.ai/stanford-radiology/\">https://unanimous.ai/stanford-radiology/</a></p>\n\n<p>I apologize if someone posted this already.</p>\n\n<p>...As presented at the 2018 SIIM Conference on Machine Intelligence in Medical Imaging, the study tasked a group of experienced radiologists with diagnosing the presence of pneumonia in chest X-rays. This is one of the most widely performed imaging procedures in the US, with more than 1 million adults hospitalized with pneumonia each year. But, despite this prevalence, accurately diagnosing X-rays is highly challenging with significant variability across radiologists. This makes it both an optimal task for applying new AI technologies, and an important problem to solve for the medical community....</p>",
      "rawMarkdown": "https://unanimous.ai/stanford-radiology/\n\nI apologize if someone posted this already.\n\n...As presented at the 2018 SIIM Conference on Machine Intelligence in Medical Imaging, the study tasked a group of experienced radiologists with diagnosing the presence of pneumonia in chest X-rays. This is one of the most widely performed imaging procedures in the US, with more than 1 million adults hospitalized with pneumonia each year. But, despite this prevalence, accurately diagnosing X-rays is highly challenging with significant variability across radiologists. This makes it both an optimal task for applying new AI technologies, and an important problem to solve for the medical community....",
      "votes": null
    },
    {
      "id": "385448",
      "postDate": "09/11/2018 03:32:21",
      "content": "<p>Thank you for this interesting article</p>",
      "rawMarkdown": "Thank you for this interesting article",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 385448,
      "author_name": "nyleve",
      "author_url": "",
      "post_date": "09/11/2018 03:32:21",
      "content": "<p>Thank you for this interesting article</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "385405": "https://unanimous.ai/stanford-radiology/\n\nI apologize if someone posted this already.\n\n...As presented at the 2018 SIIM Conference on Machine Intelligence in Medical Imaging, the study tasked a group of experienced radiologists with diagnosing the presence of pneumonia in chest X-rays. This is one of the most widely performed imaging procedures in the US, with more than 1 million adults hospitalized with pneumonia each year. But, despite this prevalence, accurately diagnosing X-rays is highly challenging with significant variability across radiologists. This makes it both an optimal task for applying new AI technologies, and an important problem to solve for the medical community....",
    "385448": "Thank you for this interesting article"
  },
  "source": "meta"
}