"Decision Trees" 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.
A graphic device used in decision analysis, series of decision options are represented as branches (hierarchical).
| Descriptor ID |
D003663
|
| MeSH Number(s) |
G17.162.500
|
| Concept/Terms |
Decision Trees- Decision Trees
- Decision Tree
- Tree, Decision
- Trees, Decision
|
Below are MeSH descriptors whose meaning is more general than "Decision Trees".
Below are MeSH descriptors whose meaning is more specific than "Decision Trees".
This graph shows the total number of publications written about "Decision Trees" by people in this website by year, and whether "Decision Trees" 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 |
|---|
| 1994 | 0 | 3 | 3 |
| 1996 | 0 | 1 | 1 |
| 1997 | 0 | 2 | 2 |
| 1998 | 1 | 4 | 5 |
| 1999 | 0 | 1 | 1 |
| 2000 | 0 | 4 | 4 |
| 2001 | 0 | 3 | 3 |
| 2002 | 0 | 8 | 8 |
| 2003 | 1 | 3 | 4 |
| 2004 | 0 | 6 | 6 |
| 2005 | 3 | 3 | 6 |
| 2006 | 1 | 7 | 8 |
| 2007 | 2 | 3 | 5 |
| 2008 | 1 | 2 | 3 |
| 2009 | 0 | 4 | 4 |
| 2010 | 1 | 3 | 4 |
| 2011 | 0 | 2 | 2 |
| 2012 | 0 | 4 | 4 |
| 2013 | 0 | 4 | 4 |
| 2014 | 0 | 3 | 3 |
| 2015 | 1 | 4 | 5 |
| 2016 | 0 | 5 | 5 |
| 2018 | 1 | 5 | 6 |
| 2019 | 1 | 3 | 4 |
| 2020 | 0 | 1 | 1 |
| 2021 | 1 | 0 | 1 |
| 2022 | 0 | 2 | 2 |
| 2023 | 0 | 1 | 1 |
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Below are the most recent publications written about "Decision Trees" by people in Profiles.
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Patients prefer free drug disposal options delivered by pharmacists at the point of care: Results of a decision tree analysis of a national factorial vignette panel survey. Int J Drug Policy. 2023 06; 116:104045.
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Exploratory Decision Trees to Predict Obesity Intervention Response among Hispanic American Youth. Child Obes. 2023 04; 19(3):194-202.
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Predicting surgical decision-making in vestibular schwannoma using tree-based machine learning. Neurosurg Focus. 2022 04; 52(4):E8.
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Optimizing Diagnostic and Staging Pathways for Suspected Lung Cancer: A Decision Analysis. Chest. 2021 12; 160(6):2304-2323.
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Machine learning-based prediction of acute severity in infants hospitalized for bronchiolitis: a multicenter prospective study. Sci Rep. 2020 07 03; 10(1):10979.
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Prospective clinical testing and experimental validation of the Pediatric Sepsis Biomarker Risk Model. Sci Transl Med. 2019 11 13; 11(518).
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Immediate Reconstruction of Oncologic Spinal Wounds Is Cost-Effective Compared with Conventional Primary Wound Closure. Plast Reconstr Surg. 2019 11; 144(5):1182-1195.
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Variability in triage practices for critically ill cancer patients: A randomized controlled trial. J Crit Care. 2019 10; 53:18-24.
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Cost-Effectiveness Analysis of Hepatitis B Virus Screening and Management in Patients With Hematologic or Solid Malignancies Anticipating Immunosuppressive Cancer Therapy. JCO Clin Cancer Inform. 2019 03; 3:1-12.
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Predictive Score for Identifying Survival and Recurrence Risk Profiles in Patients Undergoing Ventricular Tachycardia Ablation: The I-VT Score. Circ Arrhythm Electrophysiol. 2018 12; 11(12):e006730.