Lessons Learned in the Development of a Computable Phenotype for Response in Myeloproliferative Neoplasms. Academic Article uri icon

Overview

abstract

  • Determining response status in patients with myeloproliferative neoplasms is a complex problem requiring the integration of both structured and unstructured data elements from disparate information systems. By applying multiple techniques, a collaborative team of informatics professionals and research personnel were able to determine which elements were amenable to automated extraction and which required expert adjudication. With this knowledge in mind, we were able to build a system that joins together programmatically-derived and manually-abstracted data elements to facilitate response assessment - an important end point in clinical and translational research in this disease area.

publication date

  • July 26, 2018

Identity

PubMed Central ID

  • PMC6608705

Scopus Document Identifier

  • 85051130202

Digital Object Identifier (DOI)

  • 10.1109/ICHI.2018.00045

PubMed ID

  • 31276120

Additional Document Info

volume

  • 2018