2023
DOI: 10.1055/s-0043-1768721
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Clinical Informatics Approaches to Facilitate Cancer Data Sharing

Abstract: Objectives: Despite growing enthusiasm surrounding the utility of clinical informatics to improve cancer outcomes, data availability remains a persistent bottleneck to progress. Difficulty combining data with protected health information often limits our ability to aggregate larger more representative datasets for analysis. With the rise of machine learning techniques that require increasing amounts of clinical data, these barriers have magnified. Here, we review recent efforts within clinical informatics to a… Show more

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Cited by 3 publications
(2 citation statements)
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“…In the CI survey paper, Aneja et al [16] wrote that despite growing enthusiasm surrounding the utility of clinical informatics to improve cancer outcomes, data availability remains a persistent bottleneck to progress. Difficulty combining data with protected health information often limits our ability to aggregate larger more representative datasets for analysis.…”
Section: One Health and Medical Informaticsmentioning
confidence: 99%
“…In the CI survey paper, Aneja et al [16] wrote that despite growing enthusiasm surrounding the utility of clinical informatics to improve cancer outcomes, data availability remains a persistent bottleneck to progress. Difficulty combining data with protected health information often limits our ability to aggregate larger more representative datasets for analysis.…”
Section: One Health and Medical Informaticsmentioning
confidence: 99%
“…In this edition of the Cancer Informatics section, we continue to focus on translational and clinical cancer informatics, with a special emphasis on data sharing in concordance with the 2023 Yearbook theme. As pointed out by Aneja, et al [1] in the survey paper of the Cancer Informatics section of this IMIA Yearbook, "Despite growing enthusiasm surrounding the utility of clinical informatics to improve cancer outcomes, data availability remains a persistent bottleneck to progress. Difficulty combining data with protected health information often limits our ability to aggregate larger more representative datasets for analysis.…”
Section: Introductionmentioning
confidence: 99%