Literature DB >> 12182209

Decision trees: an overview and their use in medicine.

Vili Podgorelec1, Peter Kokol, Bruno Stiglic, Ivan Rozman.   

Abstract

In medical decision making (classification, diagnosing, etc.) there are many situations where decision must be made effectively and reliably. Conceptual simple decision making models with the possibility of automatic learning are the most appropriate for performing such tasks. Decision trees are a reliable and effective decision making technique that provide high classification accuracy with a simple representation of gathered knowledge and they have been used in different areas of medical decision making. In the paper we present the basic characteristics of decision trees and the successful alternatives to the traditional induction approach with the emphasis on existing and possible future applications in medicine.

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Year:  2002        PMID: 12182209     DOI: 10.1023/a:1016409317640

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  11 in total

1.  The limitations of decision trees and automatic learning in real world medical decision making.

Authors:  P Kokol; M Zorman; M M Stiglic; I Malèiae
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2.  Distributed decision support using a web-based interface: prevention of sudden cardiac death.

Authors:  G D Sanders; C G Hagerty; F A Sonnenberg; M A Hlatky; D K Owens
Journal:  Med Decis Making       Date:  1999 Apr-Jun       Impact factor: 2.583

3.  Decision trees and fuzzy logic: a comparison of models for the selection of measles vaccination strategies in Brazil.

Authors:  L Ohno-Machado; R Lacson; E Massad
Journal:  Proc AMIA Symp       Date:  2000

4.  Predicting cesarean delivery with decision tree models.

Authors:  C J Sims; L Meyn; R Caruana; R B Rao; T Mitchell; M Krohn
Journal:  Am J Obstet Gynecol       Date:  2000-11       Impact factor: 8.661

5.  Multiple signal integration by decision tree induction to detect artifacts in the neonatal intensive care unit.

Authors:  C L Tsien; I S Kohane; N McIntosh
Journal:  Artif Intell Med       Date:  2000-07       Impact factor: 5.326

6.  Towards more optimal medical diagnosing with evolutionary algorithms.

Authors:  V Podgorelec; P Kokol
Journal:  J Med Syst       Date:  2001-06       Impact factor: 4.460

Review 7.  Decision making for health care professionals: use of decision trees within the community mental health setting.

Authors:  G Bonner
Journal:  J Adv Nurs       Date:  2001-08       Impact factor: 3.187

8.  Optimization by simulated annealing.

Authors:  S Kirkpatrick; C D Gelatt; M P Vecchi
Journal:  Science       Date:  1983-05-13       Impact factor: 47.728

Review 9.  [Decision trees in psychiatric therapy].

Authors:  N Dantchev
Journal:  Encephale       Date:  1996 May-Jun       Impact factor: 1.291

10.  Decision analysis in nuclear medicine.

Authors:  S S Gambhir
Journal:  J Nucl Med       Date:  1999-09       Impact factor: 10.057

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  90 in total

1.  Decision tree for adjuvant right ventricular support in patients receiving a left ventricular assist device.

Authors:  Yajuan Wang; Marc A Simon; Pramod Bonde; Bronwyn U Harris; Jeffrey J Teuteberg; Robert L Kormos; James F Antaki
Journal:  J Heart Lung Transplant       Date:  2011-12-14       Impact factor: 10.247

2.  Improving the reliability of medical software by predicting the dangerous software modules.

Authors:  Vili Podgorelec; Marjan Hericko; Matjaz B Juric; Ivan Rozman
Journal:  J Med Syst       Date:  2005-02       Impact factor: 4.460

3.  Integrated mechanistic and data-driven modelling for multivariate analysis of signalling pathways.

Authors:  Fei Hua; Sampsa Hautaniemi; Rayka Yokoo; Douglas A Lauffenburger
Journal:  J R Soc Interface       Date:  2006-08-22       Impact factor: 4.118

4.  Predicting long-term outcome after traumatic brain injury using repeated measurements of Glasgow Coma Scale and data mining methods.

Authors:  Hsueh-Yi Lu; Tzu-Chi Li; Yong-Kwang Tu; Jui-Chang Tsai; Hong-Shiee Lai; Lu-Ting Kuo
Journal:  J Med Syst       Date:  2015-01-31       Impact factor: 4.460

5.  Ampelometric Leaf Trait and SSR Loci Selection for a Multivariate Statistical Approach in Vitis vinifera L. Biodiversity Management.

Authors:  Vittorio Alba; Carlo Bergamini; Rosalinda Genghi; Marica Gasparro; Rocco Perniola; Donato Antonacci
Journal:  Mol Biotechnol       Date:  2015-08       Impact factor: 2.695

6.  Commercial quality "awards" are not a strong indicator of quality surgical care.

Authors:  Adrienne N Cobb; Taylor R Erickson; Anai N Kothari; Emanuel Eguia; Sarah A Brownlee; Weiwei Yao; Hyunyou Choi; Victoria Greenberg; Joy Mboya; Michael Voss; Daniela Stan Raicu; Raffaella Settimi-Woods; Paul C Kuo
Journal:  Surgery       Date:  2018-05-24       Impact factor: 3.982

7.  Can Religious Beliefs be a Protective Factor for Suicidal Behavior? A Decision Tree Analysis in a Mid-Sized City in Iran, 2013.

Authors:  Mohammad Reza Baneshi; Ali Akbar Haghdoost; Farzaneh Zolala; Nouzar Nakhaee; Maryam Jalali; Reza Tabrizi; Maryam Akbari
Journal:  J Relig Health       Date:  2017-04

8.  Decision tree based diagnostic system for moderate to severe obstructive sleep apnea.

Authors:  Hua Ting; Yi-Ting Mai; Hsueh-Chen Hsu; Hui-Ching Wu; Ming-Hseng Tseng
Journal:  J Med Syst       Date:  2014-07-11       Impact factor: 4.460

9.  Medical decision support using machine learning for early detection of late-onset neonatal sepsis.

Authors:  Subramani Mani; Asli Ozdas; Constantin Aliferis; Huseyin Atakan Varol; Qingxia Chen; Randy Carnevale; Yukun Chen; Joann Romano-Keeler; Hui Nian; Jörn-Hendrik Weitkamp
Journal:  J Am Med Inform Assoc       Date:  2013-09-16       Impact factor: 4.497

10.  Stratification of the severity of critically ill patients with classification trees.

Authors:  Javier Trujillano; Mariona Badia; Luis Serviá; Jaume March; Angel Rodriguez-Pozo
Journal:  BMC Med Res Methodol       Date:  2009-12-09       Impact factor: 4.615

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