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Data Quality Assurance Tool for the Acute to Chronic Pain Signatures Study (A2CPS): An Interactive R Shiny Application.

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Title: Data Quality Assurance Tool for the Acute to Chronic Pain Signatures Study (A2CPS): An Interactive R Shiny Application.
Authors: Ansari B; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States., Sadil P; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States., Ford J; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States., Berardi G; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States.; Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, United States.; Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA, United States., Taub M; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States., Kahn A; Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, United States., Urrutia J; Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, United States., Hackman A; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States., Gherman A; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States., Lindquist MA; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Source: MedRxiv : the preprint server for health sciences [medRxiv] 2026 Jan 08. Date of Electronic Publication: 2026 Jan 08.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101767986 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: medRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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        Value: 10.64898/2026.01.07.26343620
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              Text: 2026 Jan 08
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