The future of skin cancer diagnosis: a comprehensive systematic literature review of machine learning and deep learning models-Reference-Cited by-同舟云学术

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The future of skin cancer diagnosis: a comprehensive systematic literature review of machine learning and deep learning models

Published:2024-08-28 Issue:1 Volume:11 Page:
ISSN:2331-1916
Container-title:Cogent Engineering
language:en
Short-container-title:Cogent Engineering

Author:

Adamu Shamsuddeen¹²^ORCID,Alhussian Hitham¹,Aziz Norshakirah¹,Abdulkadir Said Jadid¹,Alwadin Ayed³,Abubakar Imam Abdullahi⁴,Abdullahi Mujaheed¹,Garba Aliyu¹²,Saidu Yahaya¹

Affiliation:

1. Computer Information Science Department, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia

2. IAIICT, Ahmadu Bello University, Zaria, Nigeria

3. Computer Science Department, Community Collage King Saud University, Riyadh, Saudi Arabia

4. Universiti Brunei Darussalam (UBD), Bandar Seri Begawan, Brunei Darussalam

Funder

Yayasan UTP

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2395425

Reference96 articles.

1. Deep Learning and Machine Learning Techniques of Diagnosis Dermoscopy Images for Early Detection of Skin Diseases

2. Optimizing Hyperparameters for Improved Melanoma Classification using Metaheuristic Algorithm

3. Melanoma classification from dermatoscopy images using knowledge distillation for highly imbalanced data

4. Multiclass Skin Lesion Classification Using Hybrid Deep Features Selection and Extreme Learning Machine

5. Melanoma Skin Cancer Detection Using Image Processing and Machine Learning Techniques

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