A Matlab Toolbox for Feature Importance Ranking

Shaode Yu, Zhicheng Zhang, Xiaokun Liang, Junjie Wu, Erlei Zhang, Wenjian Qin, Yaoqin Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

More attention is paid for the feature importance ranking (FIR), in particular when high-throughput features can be extracted for intelligent diagnosis and personalized medicine. A large number of FIR methods have been proposed, while few are integrated for comparison and real-life applications. In this study, a matlab toolbox is presented and a total of 30 algorithms are collected. Moreover, the toolbox is evaluated on a database of 163 ultrasound images. To each breast lesion, 15 features are handcrafted. And to Figure out an optimal subset of features for classification, all combinations of features are tested and linear support vector machine is used for the malignancy prediction of lesions annotated in ultrasound images. At last, the effectiveness of FIR is analyzed according to performance comparison. The toolbox is available (https://github.com/NicoYuCN/matFIR). In the future work, more FIR methods, feature selection methods and machine learning classifiers will be integrated.

Original languageEnglish (US)
Title of host publication2019 International Conference on Medical Imaging Physics and Engineering, ICMIPE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728148557
DOIs
StatePublished - Nov 2019
Event2019 International Conference on Medical Imaging Physics and Engineering, ICMIPE 2019 - Shenzhen, China
Duration: Nov 22 2019Nov 24 2019

Publication series

Name2019 International Conference on Medical Imaging Physics and Engineering, ICMIPE 2019

Conference

Conference2019 International Conference on Medical Imaging Physics and Engineering, ICMIPE 2019
CountryChina
CityShenzhen
Period11/22/1911/24/19

Keywords

  • feature importance ranking
  • feature selection
  • intelligent diagnosis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Media Technology
  • Radiology Nuclear Medicine and imaging

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