A CBR framework with gradient boosting based feature selection for lung cancer subtype classification
- 1 July 2017
- journal article
- Published by Elsevier BV in Computers in Biology and Medicine
- Vol. 86, 98-106
- https://doi.org/10.1016/j.compbiomed.2017.05.010
Abstract
No abstract availableKeywords
Funding Information
- Ministry of Education, Culture and Sports of the Spanish Government (FPU15/02339)
This publication has 31 references indexed in Scilit:
- Identification of informative genes and pathways using an improved penalized support vector machine with a weighting schemeComputers in Biology and Medicine, 2016
- Non-small cell lung cancer: current treatment and future advancesTranslational Lung Cancer Research, 2016
- Non-Small Cell Lung Carcinoma: An Overview on Targeted TherapyCurrent Drug Targets, 2015
- Cancer statistics, 2015CA: A Cancer Journal for Clinicians, 2015
- Case-Based Retrieval Framework for Gene Expression DataCancer Informatics, 2015
- Immunohistochemical algorithm for differentiation of lung adenocarcinoma and squamous cell carcinoma based on large series of whole-tissue sections with validation in small specimensLaboratory Investigation, 2011
- Usage of Case-Based Reasoning, Neural Network and Adaptive Neuro-Fuzzy Inference System Classification Techniques in Breast Cancer Dataset Classification DiagnosisJournal of Medical Systems, 2010
- ANMM4CBR: a case-based reasoning method for gene expression data classificationAlgorithms for Molecular Biology, 2010
- Knowledge and intelligent computing system in medicineComputers in Biology and Medicine, 2009
- Case-Based Reasoning: Foundational Issues, Methodological Variations, and System ApproachesAI Communications, 1994