Data Cleaning: Detecting, Diagnosing, and Editing Data Abnormalities

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

The Dip Test of Unimodality

Hartigan, J. A., & Hartigan, P. M. (1985) · The Annals of Statistics · doi:10.1214/aos/1176346577 · Cited by 2,088

Statistics with Confidence

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

Short-term muscle loss after gastrointestinal cancer surgery: A two-phase study

Xu, X. (2024) · Queensland University of Technology · doi:10.5204/thesis.eprints.250840

Reconstruction of genomic and proteomic scale network structures and functions

Choudhari, J. K., Gupta, A. K., Bhatt, S., Kurmi, S., & Chouhan, U. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-22326-6.00013-4

Exploration into the equity of the impact of Exercise Referral Scheme (ERS) among different ethnic populations in the UK

Sittimart, M., Majumdar, A., & Wade, M. (2024) · Journal of Public Health · doi:10.1007/s10389-024-02362-4

Household Vulnerability and Coping Amid the COVID-19 Pandemic in Bamako, Mali: Assessing Sociodemographic Factors Associated with Household HardshipsPreprint

Muir, J. A., Onwuchekwa, U. U., Madewell, Z. J., Traoré, M., Kourouma, M., Keiri, F., Cunningham, S. A., Kotloff, K. L., Tapia, M. D., & Sow, S. O. (2024) · medRxiv · doi:10.1101/2024.11.27.24318121

Predicting Employee Under Stress Using Machine Learning

Javeriya, T. A., Kabilan, M., Manoj, G., Sree, Y. B., Jagadish, R. V. S., Mir, M. H., Debnath, S., & Girish, B. M. (2024) · International Conference on Signal Processing and Advance Research in Computing (SPARC) · doi:10.1109/sparc61891.2024.10828817

Harmony amidst dissonance: unveiling the power of open communication in resolving demarketing dilemmas

Kigen, F., & de Villiers, M. V. (2025) · Cogent Business & Management · doi:10.1080/23311975.2025.2453624

Protocol for improving equity in quantitative big data cleaning: lessons from longitudinal analysis of electronic health records from underrepresented and marginalized communities

Buchanan, Z. V., Hopkins, S. E., Boyer, B. B., & Fohner, A. E. (2025) · International Journal of Epidemiology · doi:10.1093/ije/dyaf013

Exploring Methods to Evaluate HPAI Transmission Risk in Iowa During Peak HPAI Incidence, February 2022–December 2023

Jimenez, C., & Hoepner, L. (2025) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph22030400

Data Cleaning

Calabrese, B. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-95502-7.00358-4

Editoração de dados errôneos em surveys

Henkel, K., & de Almeida, J. (2023) · Revista Gestão & Tecnologia · doi:10.20397/2177-6652/2023.v23i2.2065

Data Management in Epidemiology

Reineke, A., Pohlabeln, H., Intemann, T., & Schmidt, C. O. (2025) · Springer eBooks · doi:10.1007/978-1-4614-6625-3_48-1

Integrating Extractive Techniques and Classification Methods for Legal Document Summarization

Kumar, A., Upadhyay, U., Sharma, G., Arya, V., Alhalabi, W., Alsulami, B. S., & Gupta, B. B. (2025) · International Journal of Data Warehousing and Mining · doi:10.4018/ijdwm.379719

A Two-Phase Framework Leveraging User Feedback and Systemic Validation to Improve Post-Live Clinical Decision Support

Zhao, W., Wang, X., & Afra, K. (2025) · Applied Clinical Informatics · doi:10.1055/a-2644-7250

Corrigendum to “A pipeline for harmonising NHS Scotland laboratory data to enable national-level analyses”. [J. Biomed. Inform. 162 (2025) 104771]

Gao, C., Mumtaz, S., McCall, S., O’Sullivan, K., McGilchrist, M. M., Morales, D. R., Hall, C., Wilde, K., Mayor, C., Linksted, P., et al. (2025) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2025.104891

Overtax Detection in IT Professionals Using Machine Learning

Ravinder, L. C., Manisha, P., Sowmya, D., & Goud, V. R. (2025) · Springer proceedings in mathematics & statistics · doi:10.1007/978-3-031-84513-0_42

Assessing the impact of COVID-19 pandemic on all-cause mortality and child mortality in a population cohort of Iganga Mayuge HDSS in Eastern Uganda (2015–2021)

Kajungu, D., Nabukeera, B., Bashingwa, J. J. H., Kabudula, C. W., Barr, B. A. T., Ndyomugyenyi, D. B., Akello, M., Gyezaho, C., & Rutebemberwa, E. (2025) · Population Health Metrics · doi:10.1186/s12963-025-00435-4

The Impact of Family Functioning on Children's Adaptation During a Parent's Bone Marrow Transplantation

Spath, M. L. (2010) · IUScholarWorks (Indiana University) · doi:10.7912/c2/1244

Additional file 2 of A structural equation model of CFIR inner and outer setting constructs, organization characteristics, and national DPP enrollment

Madrigal, L., Haardörfer, R., Kegler, M. C., Piper, S., Blais, L. M., Weber, M. B., & Escoffery, C. (2024) · Figshare · doi:10.6084/m9.figshare.24586310

Additional file 1 of Effect of interventions to reduce malaria incidence among military personnel on active duty: study protocol for a cluster randomised controlled trial of the impact of etofenprox-treated uniforms, permethrin-treated uniforms and DEET insect repellent

Msellemu, D. F., Ross, A., Temu, L., Moshi, I., Hofer, L. M., Mwanziva, C. E., Kohi, Y. M., & Moore, S. J. (2021) · Figshare · doi:10.6084/m9.figshare.17058702

Additional file 3 of A structural equation model of CFIR inner and outer setting constructs, organization characteristics, and national DPP enrollment

Madrigal, L., Haardörfer, R., Kegler, M. C., Piper, S., Blais, L. M., Weber, M. B., & Escoffery, C. (2024) · Figshare · doi:10.6084/m9.figshare.26641915

Additional file 4 of A structural equation model of CFIR inner and outer setting constructs, organization characteristics, and national DPP enrollment

Madrigal, L., Haardörfer, R., Kegler, M. C., Piper, S., Blais, L. M., Weber, M. B., & Escoffery, C. (2024) · Figshare · doi:10.6084/m9.figshare.26641918

Additional file 1 of A structural equation model of CFIR inner and outer setting constructs, organization characteristics, and national DPP enrollment

Madrigal, L., Haardörfer, R., Kegler, M. C., Piper, S., Blais, L. M., Weber, M. B., & Escoffery, C. (2023) · Figshare · doi:10.6084/m9.figshare.24586213

Detection of Renal Cell Carcinoma Based on Clinical Data Using Machine Learning Approach

Zhang, B., Rao, J., Jiang, W., & Gao, Z. (2025) · IEEE International Conference on Software Engineering and Artificial Intelligence (SEAI) · doi:10.1109/seai65851.2025.11108907

Multimodal Gait Analysis Using IMU and EMG Sensors with HMM Classification to Differentiate Obese and Normal Body Types

Setiyadi, S., Rosa, M. R., Tang, N. B., Muttaqin, M. S. A., & Gumelar, M. R. H. (2025) · Journal of Novel Engineering Science and Technology · doi:10.56741/jnest.v4i03.1272

Generative AI Use Cases for Data Processing and Analysis

Kolade, O., Egbetokun, A., & Owoseni, A. (2025) · Springer eBooks · doi:10.1007/978-3-032-02440-4_4

Investigating Immersion, interactivity and Accessibility in Virtual Reality TheatrePreprint

Fahim, A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7027108

Cleaning and pre-processing of actigraphy data for physical activity and sleep research: a scoping review

Gonsalves, S. G., Zhao, J. J., Livinski, A. A., Steele, M. E., Ross, A., Fuss, T., Clevenger, K. A., & Saligan, L. N. (2026) · Physiological Measurement · doi:10.1088/1361-6579/ae3b96

CBCT Image Corpus for Tooth Implantation & Automatic Medical Report Generation

Kaur, R., Soni, P., Pawar, L., & Singh, G. (2025) · International Conference on Communication and Smart Devices (ICCoSD) · doi:10.1109/iccosd66074.2025.11348158

Self-Regulated Learning and Academic Performance in Physical Therapy Education: Exploring the Learning and Study Strategies Inventory

Kuettel, J. (2026) · Journal of Physical Therapy Education · doi:10.1097/jte.0000000000000470

Educational attainment and its impact on prevalence of sterilization among Indian women

Basak, A., Kothagattu, S., & Verma, V. (2026) · Women and Children Nursing · doi:10.1016/j.wcn.2026.02.001

Robust Random Forests for Genomic Prediction: Challenges and RemediesPreprint

Lourenço, V., Ogutu, J. O., & Piepho, H. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.30.715203

Novel class discovery in tabular data : an application to network fault diagnosis

Troisemaine, C. (2024) · theses.fr (ABES) · doi:10.70675/377074fcz84f0z4f50zb7f9z29885b812cf4

Predicting School Happiness Among Primary School Students Using Explainable Machine Learning: Evidence from a Nationally Representative Sample in TürkiyePreprint

Akar, C., & Akar, T. İ. (2026) · Research Square · doi:10.21203/rs.3.rs-9206375/v1

School Happiness in Context: Social, Behavioral, and School-Based Predictors Among Primary Students — An Explainable Machine Learning ApproachPreprint

Akar, C., & Akar, T. İ. (2026) · Research Square · doi:10.21203/rs.3.rs-9358940/v1

Patterns in Curated Celebrity Mortality Data: An Exploratory Analysis of Cardiovascular Disease Representation and Dataset Bias

Atwa, M. A., Maarouf, M. I. E. M., Atwa, B. A., & Anwar, A. E. A. (2026) · Cureus · doi:10.7759/cureus.108973

Competency-Based Cybersecurity Education: Developing Industry-Aligned Curriculum Modules

Houston, M., Chen, J., & Waldrep, D. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-22208-4_2

The serendipity paradox of artificial intelligence in oncology

Mao, Z., & Xu, B. (2026) · Intelligent Oncology · doi:10.1016/j.intonc.2026.100073

Transport policy for temporary protected people in Czechia

Galkin, A., & Beckers, J. (2026) · Transport Policy · doi:10.1016/j.tranpol.2026.104328

More Than Just Numbers: Strengthening Data Integrity Through a Community-Academic-Funder Partnership in Housing Services

Colvin, M. L., Groton, D. B., Gurdak, K., George, S., Lawrence, C., & Datta, A. D. (2026) · Human Services Organizations Management Leadership & Governance · doi:10.1080/23303131.2026.2714373

Big Data Analytics: An Assessment of Global Competitiveness and Sustainability in the Omani Context

Aro-Gordon, S., Alkalbani, M., Jeba, S., Al-Naamani, A., & Al-Haddabi, N. (2026) · Advances in Science, Technology & Innovation/Advances in science, technology & innovation · doi:10.1007/978-3-032-25471-9_6

Perspective Chapter: Digital Data Collection and Computational Integrity – Leveraging KoboToolbox and R for Real-Time Quality Assurance

Beletew, D. (2026) · IntechOpen eBooks · doi:10.5772/intechopen.1016961

Understanding the nature and effects of cognitive dissonance in demarketing contexts in the South African banking industry

Kigen, F., & de Villiers, M. V. (2026) · International Journal of Bank Marketing · doi:10.1108/ijbm-02-2025-0151

Development and validation of a machine learning-based diagnostic prediction model for frailty in older adults with diabetes

yaqingxp, Sun, Y., Zhang, L., Li, X., Zhang, Y., Liao, L., & Yang, J. (2026) · Geriatric Nursing · doi:10.1016/j.gerinurse.2026.104350

Population-based appendicular skeletal muscle mass equation: Weak association between predicted and bioimpedance-derived changes during stroke and hip-fracture rehabilitation

Yoshimura, Y., Hikuma, M., Matsumoto, A., Akasaki, S., Yoneda, K., & Nagano, F. (2026) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2026.106423

Clinical Trials Data

Burns, E. N., Smith, J. Y., Prasad, M., Boyce, D., Easter, K. B., Shiralkar, P., Doshi, R., & Wright, D. (2026) · Springer handbooks · doi:10.1007/978-3-031-92372-2_19

The Association of Gender and Socioeconomic Position with Cardiorespiratory Fitness in Adolescents

Oliphant, Q. (2015) · ScholarWorks (Walden University)

Detection and correction of influential data.

(7984088), J. M. O. (2025) · Figshare

A novel approach of data cleaning/cleansing detecting, editing

Kamble, S., & Kohle, V. (2017) · International Journal of Academic Research and Development · Cited by 2

Cleaning Method of Incorrectness Data Based on Outlier Detection

Zhu, W. (2005) · Jisuanji yingyong yanjiu · Cited by 1

The value of cleansing data.

Cashmore, J. (2005) · PubMed · Cited by 1

Consequences of inappropriate detection and removal of outlier in statistics

Petkov, G. (2022) · Bulgarian Portal for Open Science