This paper is in the following e-collection/theme issue:

Skin Cancer and Melanoma Prevention (93) Decision Support for Health Professionals (853) Imaging Informatics (154) Machine Learning (1121) Innovations in Cancer Diagnostic and Decision Support (41)

Published on in Vol 3 , No 1 (2020) :Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18438, first published .
Skin Lesion Classification With Deep Convolutional Neural Network: Process Development and Validation

Skin Lesion Classification With Deep Convolutional Neural Network: Process Development and Validation

Skin Lesion Classification With Deep Convolutional Neural Network: Process Development and Validation

Authors of this article:

Arnab Ray 1 Author Orcid Image ;   Aman Gupta 1 Author Orcid Image ;   Amutha Al 1 Author Orcid Image
Article Authors Cited by (8) Tweetations (3) Metrics

Journals

  1. Yilmaz E, Trocan M. A modified version of GoogLeNet for melanoma diagnosis. Journal of Information and Telecommunication 2021;5(3):395 View
  2. Singh L, Janghel R, Sahu S. A Deep Learning-Based Transfer Learning Framework for the Early Detection and Classification of Dermoscopic Images of Melanoma. Biomedical and Pharmacology Journal 2021;14(3):1231 View
  3. Lembhe A, Motarwar P, Patil R, Elias S. Enhancement in Skin Cancer Detection using Image Super Resolution and Convolutional Neural Network. Procedia Computer Science 2023;218:164 View
  4. Al-Azzawi W, Chenchamma G, Hamad A, Alshudukhi J, Alhamazani K, Meraf Z, Velmurugan P. Use of Radiation Circuits for Diagnosis of Melanoma Skin Cancer in Images of Skin Lesions Using Convolutional Neural Networks. Journal of Nanomaterials 2022;2022:1 View
  5. Takiddin A, Schneider J, Yang Y, Abd-Alrazaq A, Househ M. Artificial Intelligence for Skin Cancer Detection: Scoping Review. Journal of Medical Internet Research 2021;23(11):e22934 View

Books/Policy Documents

  1. Zhao Q, Chen L. Wound Healing - Recent Advances and Future Opportunities [Working Title]. View