Context-Sensitive Common Data Models for Genetic Rare Diseases - A Concept

Research output: Contribution to journalResearch articleContributedpeer-review

Abstract

Current challenges of rare diseases need to involve patients, physicians, and the research community to generate new insights on comprehensive patient cohorts. Interestingly, the integration of patient context has been insufficiently considered, but might tremendously improve the accuracy of predictive models for individual patients. Here, we conceptualized an extension of the European Platform for Rare Disease Registration data model with contextual factors. This extended model can serve as an enhanced baseline and is well-suited for analyses using artificial intelligence models for improved predictions. The study is an initial result that will develop context-sensitive common data models for genetic rare diseases.

Details

Original languageEnglish
Pages (from-to)139-140
Number of pages2
JournalStudies in health technology and informatics
Volume305
Publication statusPublished - 29 Jun 2023
Peer-reviewedYes

External IDs

ORCID /0000-0002-9888-8460/work/142254106
ORCID /0000-0002-1887-4772/work/143075278
Scopus 85164231145
ORCID /0000-0002-5577-7760/work/153152098

Keywords

Research priority areas of TU Dresden

Subject groups, research areas, subject areas according to Destatis

Keywords

  • Common Data Model, Context-Sensitive, Rare Disease, Physicians, Artificial Intelligence, Humans, Problem Solving, Rare Diseases/genetics