"Logistic Models" 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.
Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor.
Descriptor ID |
D016015
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MeSH Number(s) |
E05.318.740.500.525 E05.318.740.600.800.450 E05.318.740.750.450 E05.599.835.875 N05.715.360.750.530.480 N05.715.360.750.625.700.450 N05.715.360.750.695.470 N06.850.520.830.500.525 N06.850.520.830.600.800.450 N06.850.520.830.750.450
|
Concept/Terms |
Logistic Models- Logistic Models
- Logistic Model
- Model, Logistic
- Models, Logistic
Logit Models- Logit Models
- Logit Model
- Model, Logit
- Models, Logit
Logistic Regression- Logistic Regression
- Logistic Regressions
- Regression, Logistic
- Regressions, Logistic
|
Below are MeSH descriptors whose meaning is more general than "Logistic Models".
Below are MeSH descriptors whose meaning is more specific than "Logistic Models".
This graph shows the total number of publications written about "Logistic Models" by people in this website by year, and whether "Logistic Models" 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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1993 | 0 | 2 | 2 |
1994 | 0 | 3 | 3 |
1995 | 0 | 5 | 5 |
1996 | 0 | 8 | 8 |
1997 | 0 | 10 | 10 |
1998 | 2 | 14 | 16 |
1999 | 0 | 12 | 12 |
2000 | 0 | 15 | 15 |
2001 | 0 | 9 | 9 |
2002 | 0 | 11 | 11 |
2003 | 1 | 20 | 21 |
2004 | 1 | 18 | 19 |
2005 | 0 | 27 | 27 |
2006 | 1 | 20 | 21 |
2007 | 2 | 32 | 34 |
2008 | 0 | 32 | 32 |
2009 | 0 | 36 | 36 |
2010 | 0 | 47 | 47 |
2011 | 0 | 58 | 58 |
2012 | 1 | 50 | 51 |
2013 | 0 | 59 | 59 |
2014 | 1 | 44 | 45 |
2015 | 0 | 54 | 54 |
2016 | 0 | 56 | 56 |
2017 | 0 | 55 | 55 |
2018 | 0 | 43 | 43 |
2019 | 0 | 42 | 42 |
2020 | 0 | 33 | 33 |
2021 | 0 | 29 | 29 |
2022 | 0 | 5 | 5 |
2023 | 0 | 1 | 1 |
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Below are the most recent publications written about "Logistic Models" by people in Profiles.
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Outcomes of Older Adults With AML Treated in Community Versus Academic Centers: An Analysis of Alliance Trials. JCO Oncol Pract. 2023 06; 19(6):e877-e891.
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Using Machine Learning to Predict Likelihood and Cause of Readmission After Hospitalization for Chronic Obstructive Pulmonary Disease Exacerbation. Int J Chron Obstruct Pulmon Dis. 2022; 17:2701-2709.
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Prolonged hospital length of stay after pediatric heart transplantation: A machine learning and logistic regression predictive model from the Pediatric Heart Transplant Society. J Heart Lung Transplant. 2022 09; 41(9):1248-1257.
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A prediction model for bacteremia and transfer to intensive care in pediatric and adolescent cancer patients with febrile neutropenia. Sci Rep. 2022 05 06; 12(1):7429.
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Multicenter Development and Validation of a Model for Predicting Retention in Care Among People with HIV. AIDS Behav. 2022 Oct; 26(10):3279-3288.
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Noninvasive Prediction of Congenital Cytomegalovirus Infection After Maternal Primary Infection. Obstet Gynecol. 2022 03 01; 139(3):400-406.
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Characterization and Outcomes of Hospitalized Children With Coronavirus Disease 2019: A Report From a Multicenter, Viral Infection and Respiratory Illness Universal Study (Coronavirus Disease 2019) Registry. Crit Care Med. 2022 01 01; 50(1):e40-e51.
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Prevalence and Risk Factors of Neurologic Manifestations in Hospitalized Children Diagnosed with Acute SARS-CoV-2 or MIS-C. Pediatr Neurol. 2022 03; 128:33-44.
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Natural recovery in trichotillomania. Aust N Z J Psychiatry. 2022 10; 56(10):1357-1362.
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Non-invasive evaluation of response to obeticholic acid in patients with NASH: Results from the REGENERATE study. J Hepatol. 2022 03; 76(3):536-548.