Bias
"Bias" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.
Descriptor ID |
D015982
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MeSH Number(s) |
N05.715.350.150 N06.850.490.500
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Concept/Terms |
Bias- Bias
- Epidemiologic Biases
- Biase, Epidemiologic
- Biases, Epidemiologic
- Epidemiologic Biase
- Biases
- Bias, Epidemiologic
Ecological Bias- Ecological Bias
- Ecological Biases
- Bias, Ecological
- Fallacy, Ecological
- Ecological Fallacies
- Ecological Fallacy
- Fallacies, Ecological
- Biases, Ecological
Outcome Measurement Errors- Outcome Measurement Errors
- Error, Outcome Measurement
- Errors, Outcome Measurement
- Outcome Measurement Error
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Below are MeSH descriptors whose meaning is more general than "Bias".
Below are MeSH descriptors whose meaning is more specific than "Bias".
This graph shows the total number of publications written about "Bias" by people in this website by year, and whether "Bias" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
Year | Major Topic | Minor Topic | Total |
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1995 | 0 | 2 | 2 | 1996 | 1 | 5 | 6 | 1997 | 0 | 1 | 1 | 1998 | 0 | 1 | 1 | 1999 | 0 | 4 | 4 | 2000 | 0 | 1 | 1 | 2001 | 0 | 2 | 2 | 2002 | 0 | 2 | 2 | 2003 | 0 | 1 | 1 | 2005 | 3 | 4 | 7 | 2006 | 2 | 2 | 4 | 2007 | 0 | 7 | 7 | 2008 | 0 | 3 | 3 | 2009 | 1 | 3 | 4 | 2010 | 1 | 3 | 4 | 2011 | 0 | 6 | 6 | 2012 | 0 | 3 | 3 | 2013 | 3 | 4 | 7 | 2014 | 4 | 5 | 9 | 2015 | 1 | 4 | 5 | 2016 | 0 | 3 | 3 | 2017 | 1 | 3 | 4 | 2018 | 3 | 9 | 12 | 2019 | 4 | 3 | 7 | 2020 | 0 | 9 | 9 | 2021 | 1 | 16 | 17 | 2022 | 2 | 11 | 13 | 2023 | 0 | 4 | 4 | 2024 | 3 | 6 | 9 | 2025 | 0 | 2 | 2 |
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Below are the most recent publications written about "Bias" by people in Profiles.
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Rotter T, Kinsman LD, Alsius A, Scott SD, Lawal A, Ronellenfitsch U, Plishka C, Groot G, Woods P, Coulson C, Bakel LA, Sears K, Ross-White A, Machotta A, Schultz TJ. Clinical pathways for secondary care and the effects on professional practice, patient outcomes, length of stay and hospital costs. Cochrane Database Syst Rev. 2025 May 14; 5:CD006632.
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Byrnes JEK, Dee LE. Causal Inference With Observational Data and Unobserved Confounding Variables. Ecol Lett. 2025 Jan; 28(1):e70023.
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Lewis NM, Harker EJ, Leis A, Zhu Y, Talbot HK, Grijalva CG, Halasa N, Chappell JD, Johnson CA, Rice TW, Casey JD, Lauring AS, Gaglani M, Ghamande S, Columbus C, Steingrub JS, Shapiro NI, Duggal A, Felzer J, Prekker ME, Peltan ID, Brown SM, Hager DN, Gong MN, Mohamed A, Exline MC, Khan A, Wilson JG, Mosier J, Qadir N, Chang SY, Ginde AA, Mohr NM, Mallow C, Harris ES, Johnson NJ, Srinivasan V, Gibbs KW, Kwon JH, Vaughn IA, Ramesh M, Safdar B, DeCuir J, Surie D, Dawood FS, Ellington S, Self WH, Martin ET. Assessment and mitigation of bias in influenza and COVID-19 vaccine effectiveness analyses - IVY Network, September 1, 2022-March 30, 2023. Vaccine. 2025 Jan 01; 43(Pt 2):126492.
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Kang C, Lo JE, Zhang H, Ng SM, Lin JC, Scott IU, Kalpathy-Cramer J, Liu SA, Greenberg PB. Artificial intelligence for diagnosing exudative age-related macular degeneration. Cochrane Database Syst Rev. 2024 10 17; 10:CD015522.
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Linn S, Lawley SD, Karamched BR, Kilpatrick ZP, Josic K. Fast decisions reflect biases; slow decisions do not. Phys Rev E. 2024 Aug; 110(2-1):024305.
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Qureshi R, Naaman K, Quan NG, Mayo-Wilson E, Page MJ, Cornelius V, Chou R, Boutron I, Golder S, Bero L, Doshi P, Vassar M, Meursinge Reynders R, Li T. Development and Evaluation of a Framework for Identifying and Addressing Spin for Harms in Systematic Reviews of Interventions. Ann Intern Med. 2024 Aug; 177(8):1089-1098.
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Haller SP, Stoddard J, Cardenas SI, Dombek K, MacGillivray C, Botz-Zapp C, Bui HNT, Stavish CM, Kircanski K, Jones M, Brotman MA. Differentiating neural sensitivity and bias during face-emotion processing in youth: a computational approach. Soc Cogn Affect Neurosci. 2024 Jun 13; 19(1).
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Bakhach H, Nuffer M, Tall Bull S, Nuffer W. A Systematic Review Evaluating Cinnamon's Effects on Glucose Utilizing a Ranking System to Assess Bias and Study Quality. J Med Food. 2024 Sep; 27(9):814-823.
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Greenblott DN, Johann F, Snell JR, Gieseler H, Calderon CP, Randolph TW. Features in Backgrounds of Microscopy Images Introduce Biases in Machine Learning Analyses. J Pharm Sci. 2024 05; 113(5):1177-1189.
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Kanukula R, McKenzie JE, Bero L, Dai Z, McDonald S, Kroeger CM, Korevaar E, Forbes A, Page MJ. Investigation of bias due to selective inclusion of study effect estimates in meta-analyses of nutrition research. Res Synth Methods. 2024 Jul; 15(4):524-542.
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