Evolutionary ensemble feature selection learning for image‐based assessment of lymphedema arm volume-Reference-Cited by-同舟云学术

Evolutionary ensemble feature selection learning for image‐based assessment of lymphedema arm volume

Published:2021-08-18 Issue:1 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Yaghoobi Notash Anaram¹^ORCID,Bayat Peyman¹,Haghighat Shahpar¹²,Yaghoobi Notash Ali¹³

Affiliation:

1. Department of Computer Engineering Rasht Branch, Islamic Azad University Rasht Iran

2. Breast Cancer Research Center Motamed Cancer Institute, ACECR Tehran Iran

3. Department of Surgery, School of Medicine Tehran University of Medical Science Tehran Iran

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6334

Reference53 articles.

1. LuIM.Determination of the Accuracy and Sensitivity of Infrared Sensors for Anthropometric Lymphedema Assessment in Clinical Environments[doctoral dissertation]. Georgia Institute of Technology.2019.https://smartech.gatech.edu/bitstream/handle/1853/61696/LU‐DISSERTATION‐2019.pdf.

2. Factors Associated With Fear of Lymphedema After Treatment for Breast Cancer

3. A Comparison of Four Diagnostic Criteria for Lymphedema in a Post-Breast Cancer Population

4. Quantitative comparison between the laser scanner three-dimensional method and the circumferential method for evaluation of arm volume in patients with lymphedema

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