Automatically Evolving Interpretable Feature Vectors Using Genetic Programming for an Ensemble Classifier in Skin Cancer Detection-Reference-Cited by-同舟云学术

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Automatically Evolving Interpretable Feature Vectors Using Genetic Programming for an Ensemble Classifier in Skin Cancer Detection

Published:2024-08 Issue:3 Volume:19 Page:26-41
ISSN:1556-603X
Container-title:IEEE Computational Intelligence Magazine
language:
Short-container-title:IEEE Comput. Intell. Mag.

Author:

Ain Qurrat Ul¹^ORCID,Al-Sahaf Harith¹^ORCID,Xue Bing¹^ORCID,Zhang Mengjie¹^ORCID

Affiliation:

1. Victoria University of Wellington, Wellington, New Zealand

Funder

Science for Technological Innovation Challenge

MBIE Data Science SSIF

Victoria University of Wellington Strategic Cross-Disciplinary Fund

MBIE Endeavor Research Programme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/10207/10595483/10595537.pdf?arnumber=10595537

Reference46 articles.

1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

2. Melanoma Classification on Dermoscopy Images Using a Neural Network Ensemble Model

3. ABCD rule of dermatoscopy: A new practical method for early recognition of malignant-melanoma;Stolz;Eur. J. Dermatol.,1994

4. Dermoscopy Image Analysis: Overview and Future Directions

5. Epiluminescence Microscopy for the Diagnosis of Doubtful Melanocytic Skin Lesions

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