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FHIR IG analytics

Packagehl7.fhir.uv.fhir-for-fair
Resource TypeLibrary
IdLibrary-f4h-lib-2.json
FHIR VersionR4B

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Resources that this resource uses

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Narrative

Note: links and images are rebased to the (stated) source

FAIR4Health Study 2: 30-days readmission risk in COPD patients

ID: https://example.org/registry/f4h-study-2

Research studyDescriptionTotal number of sitesTotal number of patientsAI Algorithm
2Develop and pilot an early prediction service for 30-days readmission risk in COPD (Chronic Obstructive Pulmonary Disease) patients34.944Support Vector Machine (SVM), Logistic Regression, Decision Trees, Random Forest, Gradient Boosted Trees

Contents

Subject 1 Data https://example.org/registry/f4h-study-2-sbj-1 (application/fhir+json)

(C) Fair4Health H2020 Project.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 824666.


Source1

{
  "resourceType": "Library",
  "id": "f4h-lib-2",
  "meta": {
    "profile": [
      "http://hl7.org/fhir/uv/fhir-for-fair/StructureDefinition/Library-uv-f4f"
    ]
  },
  "text": {
    "status": "additional",
    "div": "<!-- snip (see above) -->"
  },
  "extension": [
    {
      "url": "http://hl7.org/fhir/uv/fhir-for-fair/StructureDefinition/library-relatedContent",
      "valueRelatedArtifact": {
        "extension": [
          {
            "url": "http://hl7.org/fhir/uv/fhir-for-fair/StructureDefinition/relatedArtifactClassifier",
            "valueCodeableConcept": {
              "coding": [
                {
                  "system": "http://terminology.hl7.org/CodeSystem/citation-artifact-classifier",
                  "code": "fhir-resource"
                }
              ]
            }
          },
          {
            "url": "http://hl7.org/fhir/uv/fhir-for-fair/StructureDefinition/relatedArtifactResourceReference",
            "valueReference": {
              "reference": "DocumentManifest/example-f4f-manifest"
            }
          }
        ],
        "type": "composed-of"
      }
    }
  ],
  "url": "https://example.org/registry/f4h-study-2",
  "version": "1.0.0",
  "name": "FAIR4HealthStudy2",
  "title": "FAIR4Health Study 2: 30-days readmission risk in COPD patients",
  "status": "active",
  "type": {
    "coding": [
      {
        "system": "http://terminology.hl7.org/CodeSystem/library-type",
        "code": "asset-collection"
      }
    ]
  },
  "date": "2024-01-05T17:42:10+00:00",
  "publisher": "Health Level Seven International - SOA Work Group",
  "contact": [
    {
      "name": "Health Level Seven International - SOA Work Group",
      "telecom": [
        {
          "system": "url",
          "value": "http://www.hl7.org/Special/committees/soa"
        }
      ]
    },
    {
      "name": "HL7 SOA Work Group",
      "telecom": [
        {
          "system": "url",
          "value": "http://www.hl7.org/Special/committees/soa"
        }
      ]
    }
  ],
  "useContext": [
    {
      "code": {
        "system": "http://example.org",
        "code": "number-of-patients",
        "display": "Total number of patients"
      },
      "valueQuantity": {
        "value": 4944
      }
    },
    {
      "code": {
        "system": "http://example.org",
        "code": "number-of-sites",
        "display": "Total number of sites"
      },
      "valueQuantity": {
        "value": 3
      }
    },
    {
      "code": {
        "system": "http://example.org",
        "code": "algorithm",
        "display": "AI Algorithm"
      },
      "valueCodeableConcept": {
        "text": "Support Vector Machine (SVM), Logistic Regression, Decision Trees, Random Forest, Gradient Boosted Trees"
      }
    }
  ],
  "jurisdiction": [
    {
      "coding": [
        {
          "system": "http://unstats.un.org/unsd/methods/m49/m49.htm",
          "code": "001",
          "display": "World"
        }
      ]
    }
  ],
  "purpose": "Develop and pilot an early prediction service for 30-days readmission risk in COPD (Chronic Obstructive Pulmonary Disease) patients",
  "copyright": "Fair4Health H2020 Project"
}