{
  "id": 155181,
  "title": "Where do the perfects come from? How much can I trust them?",
  "url": "/competitions/siim-isic-melanoma-classification/discussion/155181",
  "author_name": "",
  "post_date": "2020-05-31T15:24:51.235264700Z",
  "votes": 1,
  "comment_count": 2,
  "views": 0,
  "content": "<p>Does the classification of the moles into malign and benign in the training set come from biopsy or is it medical consensus? In other terms, how sure can one bee the there is no mistakes in the training data set?\nThanks</p>",
  "messages": [
    {
      "id": "868938",
      "postDate": "05/31/2020 15:24:51",
      "content": "<p>Does the classification of the moles into malign and benign in the training set come from biopsy or is it medical consensus? In other terms, how sure can one bee the there is no mistakes in the training data set?\nThanks</p>",
      "rawMarkdown": "Does the classification of the moles into malign and benign in the training set come from biopsy or is it medical consensus? In other terms, how sure can one bee the there is no mistakes in the training data set?\nThanks",
      "votes": null
    },
    {
      "id": "876625",
      "postDate": "06/06/2020 20:58:44",
      "content": "<p>Please answer this question ....\nIf I understand biology correctly, some moles turn into melanoma at some later time point, which  means that there might be false negative mistakes in the labeled data, is this correct?</p>",
      "rawMarkdown": "Please answer this question ....\nIf I understand biology correctly, some moles turn into melanoma at some later time point, which  means that there might be false negative mistakes in the labeled data, is this correct?",
      "votes": null
    },
    {
      "id": "876751",
      "postDate": "06/07/2020 02:23:43",
      "content": "<blockquote>\n  <p>The dataset contains 33,126 dermoscopic training images of unique benign and malignant skin lesions from over 2,000 patients. Each image is associated with one of these individuals using a unique patient identifier. All malignant diagnoses have been confirmed via histopathology, and benign diagnoses have been confirmed using either expert agreement, longitudinal follow-up, or histopathology. A thorough publication describing all features of this dataset is forthcoming. The dataset can be accessed at: <a href=\"https://www.kaggle.com/c/siim-isic-melanoma-classification/data\">https://www.kaggle.com/c/siim-isic-melanoma-classification/data</a></p>\n</blockquote>\n\n<p>This description comes from the webpage of the dataset source <a href=\"https://challenge2020.isic-archive.com/\">here</a></p>",
      "rawMarkdown": "&gt; The dataset contains 33,126 dermoscopic training images of unique benign and malignant skin lesions from over 2,000 patients. Each image is associated with one of these individuals using a unique patient identifier. All malignant diagnoses have been confirmed via histopathology, and benign diagnoses have been confirmed using either expert agreement, longitudinal follow-up, or histopathology. A thorough publication describing all features of this dataset is forthcoming. The dataset can be accessed at: https://www.kaggle.com/c/siim-isic-melanoma-classification/data\n\nThis description comes from the webpage of the dataset source [here][1]\n\n[1]: https://challenge2020.isic-archive.com/",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 876625,
      "author_name": "aaronalexander",
      "author_url": "",
      "post_date": "06/06/2020 20:58:44",
      "content": "<p>Please answer this question ....\nIf I understand biology correctly, some moles turn into melanoma at some later time point, which  means that there might be false negative mistakes in the labeled data, is this correct?</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 876751,
      "author_name": "cdeotte",
      "author_url": "",
      "post_date": "06/07/2020 02:23:43",
      "content": "<blockquote>\n  <p>The dataset contains 33,126 dermoscopic training images of unique benign and malignant skin lesions from over 2,000 patients. Each image is associated with one of these individuals using a unique patient identifier. All malignant diagnoses have been confirmed via histopathology, and benign diagnoses have been confirmed using either expert agreement, longitudinal follow-up, or histopathology. A thorough publication describing all features of this dataset is forthcoming. The dataset can be accessed at: <a href=\"https://www.kaggle.com/c/siim-isic-melanoma-classification/data\">https://www.kaggle.com/c/siim-isic-melanoma-classification/data</a></p>\n</blockquote>\n\n<p>This description comes from the webpage of the dataset source <a href=\"https://challenge2020.isic-archive.com/\">here</a></p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "868938": "Does the classification of the moles into malign and benign in the training set come from biopsy or is it medical consensus? In other terms, how sure can one bee the there is no mistakes in the training data set?\nThanks",
    "876625": "Please answer this question ....\nIf I understand biology correctly, some moles turn into melanoma at some later time point, which  means that there might be false negative mistakes in the labeled data, is this correct?",
    "876751": "&gt; The dataset contains 33,126 dermoscopic training images of unique benign and malignant skin lesions from over 2,000 patients. Each image is associated with one of these individuals using a unique patient identifier. All malignant diagnoses have been confirmed via histopathology, and benign diagnoses have been confirmed using either expert agreement, longitudinal follow-up, or histopathology. A thorough publication describing all features of this dataset is forthcoming. The dataset can be accessed at: https://www.kaggle.com/c/siim-isic-melanoma-classification/data\n\nThis description comes from the webpage of the dataset source [here][1]\n\n[1]: https://challenge2020.isic-archive.com/"
  },
  "source": "meta"
}