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ALUDWIG

info
All the items of this scoring system can be extracted automatically from the image. Thanks to this, you don't need to provide the questionnaireResponse.

What is ALUDWIG?​

ALUDWIG, short for Automatic Ludwig, represents a revolutionary advancement in the assessment of female pattern baldness, specifically androgenic alopecia. It employs sophisticated artificial intelligence algorithms to swiftly and accurately determine the stage of hair loss, ranging from stages I to III, based on the renowned Ludwig scale.

Body site​

To initiate the ALUDWIG assessment, a single photograph of the head's top region (HEAD_TOP) is required.

How to take pictures​

Ensuring the capture of high-quality photos is paramount to achieving optimal algorithm performance. A comprehensive guide featuring essential tips for image acquisition is available to assist in this endeavor. This section is exclusively dedicated to detailing the photo capture process, with the singular objective of attaining the finest outcomes in ALUDWIG computation.

How does ALUDWIG work?​

At the core of ALUDWIG's functionality lies cutting-edge convolutional neural networks (CNNs) meticulously trained on an extensive dataset. This dataset comprises thousands of meticulously annotated images curated by a panel of seasoned experts. Through intricate analysis, the algorithm quantifies both low and high hair density, ultimately computing a percentage of hair loss. This percentage corresponds to a grade on the Ludwig scale, providing invaluable insights into the extent of hair loss experienced by the individual.

Request ALUDWIG score​

Relevant keys in the body of the request
{
  "requestId": "90925097-820b-403d-a75d-4cd989903df1",
  "data": {
    "type": "image",
    "modality": "clinical",
    "operator": "Practitioner",
    "bodySite": "HEAD_TOP",
    "knownConditionForThisImage": {
      "conclusion": "Androgenetic alopecia"
    },
    "subject": {
      "identifier": "6ec724a0-6fa3-11eb-a15f-0242ac160004",
      "gender": "f",
      "height": 156,
      "weight": 56,
      "birthdate": "1995-04-24",
      "generalPractitioner": {
        "identifier": "44f89a8c-654d-11eb-9c8a-0242ac160004"
      },
      "managingOrganization": {
        "identifier": "b13cd636-327b-11ec-86b0-0242ac180004",
        "display": "Hospital Central"
      }
    },
    "scoringSystems": ["ALUDWIG", "DLQI"],
    "questionnaireResponse": {
      "DLQI": {
        "question1": 2,
        "question2": 3,
        "question3": 1,
        "question4": 2,
        "question5": 1,
        "question6": 2,
        "question7": 2,
        "question8": 2,
        "question9": 3,
        "question10": 2
      }
    },
    "content": "base64 image"
  }
}
Check out the documentation
It is important that you check out the section Output of this documentation to understand how you should build the request and what will the response look like. Keep in mind that this is a snippet of a larger JSON file.

The bodySite must be specified as HEAD_TOP.

Response​

Relevant keys in the body of the response
"evolution": {
  "domains": {
    "ALUDWIG": {
      "explainabilityMedia": {
        "content": "base 64 image",
        "detections": null
      },
      "facets": {
        "alopecia": {
          "intensity": 40,
          "value": 40
        }
      },
      "grade": {
        "category": "Grade III",
        "score": 40
      }
    }
  }
}
Check out the documentation
It is important that you check out the section Output of this documentation to understand how you should build the request and what will the response look like. Keep in mind that this is a snippet of a larger JSON file.