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Decision tree classifiers for automated medical diagnosis

Azar, Ahmad Taher, El-Metwally, Shereen M.·2013·Neural Computing and Applications

DOI 10.1007/s00521-012-1196-7

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Self-citation
Breast Cancer Detection: Comparative Analysis of Machine Learning Classification Techniques
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Self-citation

Authors: Azar, A. T., & El-Metwally, S. M.
Affiliations: Misr University for Science and Technology (EG)
Cairo University (EG)
Corresponding author: Azar, Ahmad Taher
ORCID: Azar, Ahmad Taher
El-Metwally, Shereen M.
Venue: Neural Computing and Applications
Publisher: Springer Science and Business Media LLC
Published: 2012-10-07
Volume: 23
Issue: 7-8
Pages: 2387-2403
ISSN: 0941-0643 (ISSN-L)
1433-3058
DOI: 10.1007/s00521-012-1196-7
OpenAlex: W1982067074
Cited by: 242
References: 86
Citations by year: 2026: 9 · 2025: 29 · 2024: 29 · 2023: 27 · 2022: 26 · 2021: 24 · 2020: 28 · 2019: 18 · 2018: 15 · 2017: 19 · 2016: 8 · 2015: 6 · 2014: 3 · 2013: 1
FWCI: 5.20
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Neural Computing and Applications (publishedVersion)
Funders: National Cancer Institute
Topics: Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
Keywords: breast cancer detection, decision tree classification, boosted decision trees, decision tree forest, clinical decision support systems, automated medical diagnosis, Wisconsin Breast Cancer dataset, classifier comparison

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