Conference
Computable phenotypes for cohort identification: core content for a new class of FAIR Digital Objects
| العنوان: | Computable phenotypes for cohort identification: core content for a new class of FAIR Digital Objects |
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| المؤلفون: | Conte,Marisa, Flynn,Allen, Boisvert,Peter, Landis-Lewis,Zach, Richesson,Rachel, Friedman,Charles |
| المصدر: | Research Ideas and Outcomes 8: e95856 |
| بيانات النشر: | Pensoft Publishers |
| سنة النشر: | 2022 |
| المجموعة: | Pensoft Publishers |
| مصطلحات موضوعية: | computable biomedical knowledge, portability, reuse |
| الوصف: | IntroductionWe present current work to develop and define a class of digital objects that facilitates patient cohort identification for clinical studies, such that these objects are Findable, Accessible, Interoperable, and Reusable (FAIR) (Wilkinson et al. 2016). Developing this class of FAIR Digital Objects (FDOs) builds on the work of several years to develop the Knowledge Grid (https://kgrid.org/), which facilitates the development, description and implementation of biomedical knowledge packaged in machine-readable and machine-executable formats (Flynn et al. 2018). Additionally, this work aligns with the goals of the Mobilizing Computable Biomedical Knowledge (MCBK) community (https://mobilizecbk.med.umich.edu/) (Mobilizing Computable Biomedical Knowledge 2018). In this abstract, we describe our work to develop a FDO carrying a computable phenotype.Defining computable phenotypesIn biomedical informatics, 'phenotyping' describes a data-driven approach to identifying a group of individuals sharing observable characteristics of interest, generally related to a disease or condition, and a 'computable phenotype' (CP) is a machine-processable expression of a phenotypic pattern of these characteristics (Hripcsak and Albers 2018). For the purposes of this work, we are interested in CPs derived from data contained in electronic health record (EHR) systems. This includes both structured data, e.g. codes for diseases, diagnoses, procedures, or laboratory tests, and unstructured data, e.g. free text including patient histories, clinical observations, discharge summaries, and reports. Thus, we define computable phenotype FDOs (CP-FDOs) as a class of FDO that packages an executable EHR-derived CP together with documentation needed to implement and use it effectively for creating cohorts of individuals with similar observable characteristics from EHR data sets.Importance of portable and FAIR CPsThere is tremendous excitement for using real-world EHR data to discover important findings about human health and well-being. ... |
| نوع الوثيقة: | conference object |
| وصف الملف: | text/html |
| اللغة: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/eissn/2367-7163 |
| DOI: | 10.3897/rio.8.e95856 |
| الاتاحة: | https://doi.org/10.3897/rio.8.e95856 https://riojournal.com/article/95856/ |
| Rights: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.BE160CD1 |
| قاعدة البيانات: | BASE |
| DOI: | 10.3897/rio.8.e95856 |
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