Data Quality in Clinical Research

Nahm, Meredith

doi:10.1007/978-1-84882-448-5_10

Cited by 32Data Quality and ManagementElectronic Health Records SystemsResearch Data Management Practices

Data Quality in Clinical Research

Nahm, Meredith·2012·Health Informatics

DOI 10.1007/978-1-84882-448-5_10

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Representativeness is a crucial property for secondary use of data in clinical studies or when reusing medical data as training data for ML applications.
“In particular, representativeness is often not a factor86,87 while it is a crucial property for secondary use of data in clinical studies88 or when reusing medical data as training data for ML applications.”
From The METRIC-framework for assessing data quality for trustworthy AI in medicine: A systematic review (2024) · cites this paper as [88]

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Authors: Nahm, M.
Affiliations: Duke University (US)
Corresponding author: Nahm, Meredith
Venue: Health Informatics
Publisher: Springer London
Published: 2012
Pages: 175-201
ISSN: 1431-1917 (ISSN-L)
DOI: 10.1007/978-1-84882-448-5_10
OpenAlex: W2218029811
Cited by: 32
References: 75
Citations by year: 2024: 1 · 2023: 1 · 2022: 5 · 2021: 6 · 2020: 7 · 2019: 1 · 2018: 2 · 2017: 3 · 2016: 2 · 2015: 2 · 2013: 1 · 2012: 1
FWCI: 3.73
Type: book chapter
Language: en
Open access: closed
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Computers in health care (publishedVersion)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Data Quality and Management
Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
Keywords: data quality, clinical research data, data collection, data processing, data quality dimensions, data quality framework, clinical research informatics, data management

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