Context-Sensitive Common Data Models for Genetic Rare Diseases - A Concept
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
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
Originalsprache | Englisch |
---|---|
Seiten (von - bis) | 139-140 |
Seitenumfang | 2 |
Fachzeitschrift | Studies in health technology and informatics |
Jahrgang | 305 |
Publikationsstatus | Veröffentlicht - 29 Juni 2023 |
Peer-Review-Status | Ja |
Externe IDs
ORCID | /0000-0002-9888-8460/work/142254106 |
---|---|
ORCID | /0000-0002-1887-4772/work/143075278 |
Scopus | 85164231145 |
ORCID | /0000-0002-5577-7760/work/153152098 |
Schlagworte
Forschungsprofillinien der TU Dresden
Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis
ASJC Scopus Sachgebiete
Schlagwörter
- Common Data Model, Context-Sensitive, Rare Disease, Physicians, Artificial Intelligence, Humans, Problem Solving, Rare Diseases/genetics