FHIR for FAIR - FHIR Implementation Guide, published by Health Level Seven International - SOA Work Group. This guide is not an authorized publication; it is the continuous build for version 1.0.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7/fhir-for-fair/ and changes regularly. See the Directory of published versions
Active as of 2021-10-10 |
ID: https://example.org/registry/fair4health
Research study | Description | Total number of sites | Total number of patients | AI Algorithm |
1 | Identification of multimorbidity patterns and polypharmacy correlation on the risk of mortality in elderly, and demonstrate the reproducibility of research | 5 | 11.486 | FP Growth |
2 | Develop and pilot an early prediction service for 30-days readmission risk in COPD (Chronic Obstructive Pulmonary Disease) patients | 3 | 4.944 | Support Vector Machine (SVM), Logistic Regression, Decision Trees, Random Forest, Gradient Boosted Trees |
Platform access point: https://portal.fair4health.eu/
Common Data model: https://github.com/fair4health/common-data-model
Owner: FAIR4Health Consortium.
FAIR metadata repository: https://github.com/fair4health/metadata
documentation | Web site | Publication Site | FAIR4Health Platform access point | https://portal.fair4health.eu/ |
depends-on | Model | Common Data model | Common models, expressed as HL7 FHIR profiles, used by the FAIR4Health project in the FAIRification process | https://github.com/fair4health/common-data-model |
depends-on | Metadata | Metadata repository | FAIR4Health FAIR metadata repository | https://github.com/fair4health/metadata |
Identification of multimorbidity patterns and polypharmacy correlation on the risk of mortality in elderly, and demonstrate the reproducibility of research: https://example.org/registry/f4h-study-1
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Develop and pilot an early prediction service for 30-days readmission risk in COPD (Chronic Obstructive Pulmonary Disease) patients: https://example.org/registry/f4h-study-2
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(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.