The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Data Cleaning: Detecting, Diagnosing, and Editing Data Abnormalities
Open accessAbstract
Inlier: Data value falling within
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures


Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Ambulatory data measured with wearable sensors, mobile phones, and surveys tend to be noisy.”
From Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (2018) · cites this paper as [31]
Experimental — accuracy not yet measuredIn the citing paper
“A clear and transparent description of data cleaning methods is important, as choice of methods could affect study findings, repeatability of the study, and reproducibility of study findings [50].”
From The Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) statement. (2015) · cites this paper as [50]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neural Networks: A Comprehensive Foundation
Haykin, S. (1998) · Cited by 30,070
Analysis of Incomplete Multivariate Data
Booth, D. E., & Schafer, J. L. (2000) · Technometrics · doi:10.2307/1271466 · Cited by 5,627
Classical and Modern Regression With Applications.
Steinhorst, R. K., & Myers, R. H. (1988) · Journal of the American Statistical Association · doi:10.2307/2288958 · Cited by 3,691
Hartigan, J. A., & Hartigan, P. M. (1985) · The Annals of Statistics · doi:10.1214/aos/1176346577 · Cited by 2,088
Smithson, M. J. (2000) · SAGE Publications Ltd eBooks · doi:10.4135/9781446218525 · Cited by 1,871
A product perspective on total data quality management
Wang, R. Y. (1998) · Communications of the ACM · doi:10.1145/269012.269022 · Cited by 911
Identifying Multiple Outliers in Multivariate Data
Hadi, A. S. (1992) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1992.tb01449.x · Cited by 775
How to Detect and Handle Outliers
Crosby, T. A., Iglewicz, B., & Hoaglin, D. C. (1994) · Technometrics · doi:10.2307/1269377 · Cited by 764
Post-randomisation exclusions: the intention to treat principle and excluding patients from analysis
Fergusson, D., Aaron, S. D., Guyatt, G., & Hébert, P. (2002) · BMJ · doi:10.1136/bmj.325.7365.652 · Cited by 708
Attrition in longitudinal studies
Twisk, J., & de Vente, W. (2002) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(01)00476-0 · Cited by 527
Research works printed but not linked: 1
- Gonzalez, 1975, J Am Stat Assoc, 70, 6
Cited by
Sorted by citations
Items 301–400 of 446
ŞEN, S., & Sapancı, A. (2024) · Journal of Dependence · doi:10.51982/bagimli.1406354 · Cited by 2
Bendigiri, P., & Rao, P. (2024) · International Journal of Energy Sector Management · doi:10.1108/ijesm-07-2024-0047 · Cited by 1
EMIS, drop-in and dropout in Eritrea
Kamuli, K. E., & Oketch, M. (2025) · Journal of International Cooperation in Education · doi:10.1108/jice-02-2024-0009 · Cited by 1
Schurz, A. P., Deliens, T., Liechti, M., Vanroose, M., Clijsen, R., Nijs, J., Malfliet, A., Bogaert, W. V., Clarys, P., Baur, H., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2024-098272 · Cited by 1
From Archives to Artifacts: A Forensic Analysis of Noisy Data
Woods, D. (2025) · Chinese Political Science Review · doi:10.1007/s41111-025-00309-y · Cited by 1
Alduais, A. M. S., Alfadda, H. A., & Alarifi, H. S. (2025) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580251382005 · Cited by 1
Feng, G., Wang, H., Zhang, T., Wang, L., Huang, L., Wei, Y., Chen, Z., Sun, F., & Xu, H. (2026) · The Innovation Medicine · doi:10.59717/j.xinn-med.2026.100197 · Cited by 1
An empirical characterization of the accuracy of software process elicitation
Crabtree, C. A., Norcio, A. F., & Seaman, C. B. (2011) · International Conference on Software and System Process · doi:10.1145/1987875.1987892 · Cited by 1
Lam, E., Rolle, I., Shin, M., & Lee, K. A. (2013) · Preventing Chronic Disease · doi:10.5888/pcd10.120202 · Cited by 1
Data Quality Assessment and Recommendations to Improve the Quality of Hemodialysis Database
Firouraghi, N., Jahromi, S. E., Sami, A., Morvaridi, M. R., & Sharifian, R. (2018) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 1
Benchimol, E. I., Smeeth, L. L., Guttmann, A., Harron, K. L., Moher, D., Petersen, I., Sørensen, H. T., Januel, J., von Elm, E. B., & Langan, S. (2019) · Canadian Medical Association Journal · doi:10.1503/cmaj.181309 · Cited by 2
Billing and Review Perspectives in Healthcare
Fredrickson, J. (2019) · Advances in healthcare information systems and administration book series · doi:10.4018/978-1-7998-2310-0.ch002 · Cited by 1
Quality Data Is Power: Data Management and Monitoring
Baker, F. A. (2022) · Springer eBooks · doi:10.1007/978-3-031-18085-9_7 · Cited by 1
Data management and SPSS environment
Faizi, N., & Alvi, Y. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-18550-2.00008-6 · Cited by 1
Predicting Stress at Workplace using Machine Learning Techniques
Kapoor, A., & Goel, S. (2023) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt56998.2023.10306720 · Cited by 1
Scalable fuzzy multivariate outliers identification towards big data applications
Touny, H. M., Moussa, A. S., & Hadi, A. S. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.111444 · Cited by 1
Coping with Exploitative Labour Market: A Case of Sri Lankan migrants in Bahrain
Idrees, M. A. M., Eid, I. M., & Rokis, R. (2023) · IIUM JOURNAL OF HUMAN SCIENCES · doi:10.31436/ijohs.v5i1.274 · Cited by 1
Descriptive Analysis and Interpretation
Monsen, K. A. (2024) · Springer eBooks · doi:10.1007/978-3-031-54111-7_6 · Cited by 1
Benalcázar, M. C. A., Paredes, M. F. J., & Hidalgo, O. M. R. (2025) · Ciencia Latina Revista Científica Multidisciplinar · doi:10.37811/cl_rcm.v8i6.15653 · Cited by 1
Standardizing patent data cleaning in a university technology transfer office
Srihari, M. M., & Mathew, M. (2014) · NOT FOUND REPOSITORY (Indian Institute of Science Bangalore) · Cited by 1
Preparing Archaeological Data for Spatial Analysis
Gupta, N. (2020) · Open Collections · doi:10.14288/1.0388697 · Cited by 1
Hugon, F., Liquet, B., & d'Amico, F. (2020) · Remote Sensing · doi:10.3390/rs12182908 · Cited by 1
Data Cleaning Techniques in Detecting Tendencies in Software Engineering
Georgieva, P., Nikolova, E. P., & Orozova, D. (2020) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.23919/mipro48935.2020.9245416 · Cited by 1
Nair, R. D., Odrovakavula, L., Mohammadnezhad, M., Reddy, K. V. R., Gohil, D. A., & Sami, S. S. (2021) · Global Journal of Health Science · doi:10.5539/gjhs.v13n3p23 · Cited by 1
An Analysis of blood donors and Hepatitis C patients by using big data techniques
Sivachandran, M., & Krishnakumar, D. T. (2021) · International Conference on Computing, Communication and Control System (I3CAC) · doi:10.4108/eai.7-6-2021.2308658 · Cited by 1
Trevethan, R., & Ma, K. (2021) · Frontiers in Education · doi:10.3389/feduc.2021.723141 · Cited by 1
Asking the Right Questions: Insights into Assessing Intercultural Sensitivity
Balakrishnan, A. (2015) · Scholarship@Western (Western University) · Cited by 1
Exploratory Data Analysis Faktor Pengaruh Kesehatan Mental di Tempat Kerja
Maringka, R. C., & Kusnawi, K. (2021) · CogITo Smart Journal · doi:10.31154/cogito.v7i2.312.215-226 · Cited by 1
USING TECHNOLOGY TO CHANGE ADULT SEDENTARY BEHAVIOUR, PHYSICAL ACTIVITY LEVELS AND TOTAL WELLNESS
Barwais, F. A. (2013) · doi:10.13140/rg.2.2.35623.75681 · Cited by 1
Clarke, A. (2015) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · Cited by 1
Climate change attitudes within the field of power in Norway: a Bourdieusian perspective
Karamali, A. (2019) · NORA - Norwegian Open Research Archives · Cited by 1
Converting threats into opportunities predicting medical error reporting behavior.
Rogers, W. (2020) · doi:10.18297/etd/3368 · Cited by 1
A Modular Task Orientated Approach for the Analysis of Large DatasetsPreprint
Palmer, P. J., Henshaw, M., & Lock, R. (2019) · doi:10.31219/osf.io/ys2vw · Cited by 1
The influence of workplace skills plan on human capital development at the eThekweni Municipality
Madonda, S. E. (2021) · doi:10.51415/10321/4307 · Cited by 1
Cogan, A. M., Roberts, P. S., & Mallinson, T. (2024) · OTJR Occupational Therapy Journal of Research · doi:10.1177/15394492241246544 · Cited by 1
A Merging System for Integrated Person-Centric Information Systems
Jain, S. (2021) · Digital Commons - USU (Utah State University) · doi:10.26076/a89c-6534
McCoy, A. B., Ottenbacher, A. J., Sittig, D. F., & Etchegaray, J. M. (2012) · HERD Health Environments Research & Design Journal · doi:10.1177/193758671200500412
Managing Data Integrity as Part of Master Data Management
Vihavainen, K. (2014) · Theseus (Ammattikorkeakoulujen)
Gomez, A. (2015) · CSUN ScholarWorks (California State University, Northridge)
Impact of Energy Efficiency Improvement on Productivity in Indonesia Manufacturing Sector
Armundito, E. (2015) · Hiroshima University Acedemic Information Repository (Hiroshima University)
Predictors of Likeliness to Engage in Radical Animal Rights and Environmental Activism
McKenzie, P. (2016) · ScholarWorks (Walden University)
Social Network Correlates of HCV and HIV Transmission Risk Behaviors among Injecting Drug Users
Reyes-Ortíz, V. E. (2015) · ScholarWorks (Walden University)
Knowledge and Information: An Unrestricted View
Firoozye, N. B., & Ariff, F. (2016) · Palgrave Macmillan UK eBooks · doi:10.1057/9781137334541_7
Ibeachu, C. (2016) · CLOK (University of Central Lancashire)
Rezvani, Z. (2017) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Descriptive Analysis and Interpretation
Monsen, K. A. (2017) · Springer eBooks · doi:10.1007/978-3-319-61246-1_5
Front-End Cost Estimation by Selective Case-Based Reasoning for Building Construction Projects
안요섭 (2016) · Seoul National University Open Repository (Seoul National University)
The Alternate Futures of Precision Medicine
Berman, J. J. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-814393-3.00009-3
Bilgin, M., & Çolak, E. (2018) · OSMANGAZİ JOURNAL OF MEDICINE · doi:10.20515/otd.409043
Error Detection in a Large-Scale Lexical TaxonomyPreprint
Liu, S., & Wang, H. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1808.01690
Tracing the outlier: digital objects and algorithmic sorting in Rossella Biscotti’s Other
Herrie, M. B. (2019) · Journal of AESTHETICS & CULTURE · doi:10.1080/20004214.2019.1605801
Predicting the required pre-surgery blood volume in surgical patients based on machine learningPreprint
Li, R., Han, X., Sun, L., Feng, Y.-N., Sun, X., He, X., Zhang, Y., Zhu, H., Zhao, D., Dai, C., et al. (2019) · medRxiv · doi:10.1101/19008045
Functional outcomes of anterior cruciate ligament reconstruction surgery
Gabr, A. (2019) · UCL Discovery (University College London)
Oswald, C. (2020) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/68ye-rt64
Berman, J. J. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-803781-2.00002-3
Decision Tree to Predict the Color Quality of Refined Bleached Deodorized Palm Oil (RBPO)
Sembiring, M. T., Chailes, S., & Sawaluddin, S. (2020) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/851/1/012008
Ikeshoji, M. A., de Souza, A. N., da Costa, P., Gastaldello, D. S., Papa, J. P., & Gonzales, C. G. (2020) · Anais do ... Simpósio Brasileiro de Sistemas Elétricos · doi:10.48011/sbse.v1i1.2192
Establishing a Sorting Protocol for Healthcare Databases
Ghabi, E. M., Farah, W., Abboud, M., Chalhoub, E., Ziadé, N., Annesi‐Maesano, I., Habib, L. A., & Nakhlé, M. M. (2021) · Journal of Public Health Research · doi:10.4081/jphr.2021.1722
Review on Data Analysis of CryptocurrencyPreprint
Keshari, P., Koley, S., Mandal, K. K., & Singh, P. K. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3350318
Advanced Computer Network for Healthcare Sector – Liver Function Diagnosis
Janardhana, K., Rajasekar, P., Shali, A., Vijayaragavan, M., & David, D. S. (2021) · International Conference on Computing, Communication and Control System (I3CAC) · doi:10.4108/eai.7-6-2021.2308797
Millington, S., Edwards, S., Clark, R. A., Dekker, G., & Arstall, M. A. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255070 · Cited by 1
Singh, G., Soman, B., & Mitra, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.09963
Visualização de Informação como Ferramenta de Apoio à Curadoria de Dados em Coleções Biológicas
Sá, A. M. E., Oliveira, F., & SEREJO, C. S. (2021) · Museologia & Interdisciplinaridade · doi:10.26512/museologia.v10iespecial.36709
Mise en forme et contrôle qualité de données, l’informatique au service de l’écologie
Hugon, F., Navarro, X., RODRIGUEZ, M., NEVES, G. D., Berroneau, M., & d'Amico, F. (2022) · Naturae · doi:10.5852/naturae2022a2
The Effect of Facial Attributes in Identifying Gender Using Facial Recognition
Ariq, A. M., Tri, Y. D., Uzh, Z. D., & Napitupulu, H. (2021) · International Conference on Artificial Intelligence and Big Data Analytics (ICAIBDA) · doi:10.1109/icaibda53487.2021.9689705
(2018) · Wiley eBooks · doi:10.1002/9781119341901.refs
Use Data Mining Cleansing to Prepare Data for Strategic Decisions
Sikibi, M. (2022) · Artificial intelligence · doi:10.5772/intechopen.99144
Research Policy of the Research Data Management in Pharmacy Practice
Alomi, Y. A., Al-Najjar, A. H., Abushomi, H. Q. A., Almadany, M. H., & Almasoudi, A. H. (2022) · International Journal of Pharmacology and Clinical Sciences · doi:10.5530/ijpcs.2022.11.5
Sun, Z., Scott, I., Bell, S., Zhang, X., & Wang, L. (2020) · Research Square · doi:10.21203/rs.3.rs-54597/v1
(2013) · Elsevier eBooks · doi:10.1016/b978-0-12-404576-7.09978-0
Identification, Deidentification, and Reidentification
Berman, J. J. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-815609-4.00003-0
(2015) · Elsevier eBooks · doi:10.1016/b978-0-12-802882-7.00016-6
Gonzalez, J. C. (2022) · Open Access Victoria University of Wellington | Te Herenga Waka (Figshare) · doi:10.26686/wgtn.20579568 · Cited by 1
The Research on Dynamics in Phone Sales Marketing Campaign Based on Machine Learning
Lai, Z. (2022) · BCP Business & Management · doi:10.54691/bcpbm.v32i.2967
Husk å vaske dataene før bruk!
Stavseth, M. R. (2023) · Tidsskrift for Den norske legeforening · doi:10.4045/tidsskr.22.0825
Propuesta metodológica para la validación de bases de datos aplicada a las ciencias de la salud
Otzen, T., Manterola, C., García-Méndez, N., Varela, K., & Quiroz, G. (2022) · Revista chilena de infectología · doi:10.4067/s0716-10182022000500630
MARKETING AUDIT AND ITS IMPACT ON SMALL BUSINESS IN KAZAKHSTAN
Turekhanova, A. О., & Smykova, M. (2023) · Central Asian Economic Review · doi:10.52821/2789-4401-2022-6-7-20
Roderick, S. (2023) · Cronfa (Swansea University) · doi:10.23889/suthesis.63664
Deep Neural Networks are Utilized in Energy Management Systems for identifying Theft of Electricity
Ruthwik, S. M. (2023) · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · doi:10.55041/ijsrem25133
Towards Rough Set Theory for Outliers Detection in Questionnaire Data
Uher, V., & Dráždilová, P. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-42823-4_23
An Improved Check Digit-based Participant Identification System for Human Biorepositories
Chu, M., Kang, G., & Ryu, K. H. (2023) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc58517.2023.10317197
Baglole, J. S. (2023) · Carleton University's Institutional Repository (MacOdrum Library, Carleton University) · doi:10.22215/etd/2023-15840
Deep Learning Models to Estimate and Predict the Solar Irradiation in Brazil
de Souza, W. A., Alonso, A. M. S., Bernardino, L. G. R., Castoldi, M. F., do Nascimento, C. F., & Marafão, F. P. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-48652-4_5
Hibbett, M. (2024) · Palgrave studies in comics and graphic novels · doi:10.1007/978-3-031-45173-7_3
Ten Tips to Design a Better Case Record Form
Krishnan, V. (2024) · Journal of Medical Evidence · doi:10.4103/jme.jme_150_23
Đăng, Đ. H. (2024) · Tạp chí Khoa học Trường Đại học Mở Hà Nội · doi:10.59266/houjs.2023.322
Special Considerations in Big Data Analysis
Berman, J. J. (2013) · Elsevier eBooks · doi:10.1016/b978-0-12-404576-7.00010-1
Alexander, G. L., Poghosyan, L., Zhao, Y., Hobensack, M., Kisselev, S., Norful, A. A., McHugh, J., Wise, K., Schrimpf, M., Kolanowski, A. M., et al. (2024) · JMIR Research Protocols · doi:10.2196/56170
Metadata
- Authors
- Van den Broeck, J., Argeseanu Cunningham, S., Eeckels, R., & Herbst, K.
- Affiliations
- University of Pennsylvania (US)
- ORCID
- Herbst, Kobus
- Venue
- PLoS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2005-09-06
- Volume
- 2
- Issue
- 10
- Pages
- e267
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- PMC
- PMC1198040
- OpenAlex
- W1971935224
- Cited by
- 446
- References
- 18
- Citations by year
- 2026: 21 · 2025: 39 · 2024: 35 · 2023: 35 · 2022: 32 · 2021: 47 · 2020: 40 · 2019: 47 · 2018: 36 · 2017: 23 · 2016: 25 · 2015: 17 · 2014: 9 · 2013: 13 · 2012: 5
- FWCI
- 3.71
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Wellcome Trust (063009)
- Topics
- Physical Sciences › Computer Science › Information Systems › Data Quality and Management
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
- Keywords
- data cleaning, data quality, data anomalies, outlier detection, data editing, data validation
- MeSH terms
- Ethics, Professional, Humans, Peer Review, Statistics as Topic, Reproducibility of Results, Epidemiologic Studies, Guidelines as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review