Machine Learning in Melanoma Diagnosis. Limitations About to be Overcome-Reference-Cited by-同舟云学术

Machine Learning in Melanoma Diagnosis. Limitations About to be Overcome

Published:2020-05 Issue:4 Volume:111 Page:313-316
ISSN:1578-2190
Container-title:Actas Dermo-Sifiliográficas (English Edition)
language:en
Short-container-title:Actas Dermo-Sifiliográficas (English Edition)

Author:

González-Cruz C.,Jofre M.A.,Podlipnik S.,Combalia M.,Gareau D.,Gamboa M.,Vallone M.G.,Faride Barragán-Estudillo Z.,Tamez-Peña A.L.,Montoya J.,América Jesús-Silva M.,Carrera C.,Malvehy J.,Puig S.

Funder

Fondo de Investigaciones Sanitarias

CIBER de Enfermedades Raras of the Instituto de Salud Carlos III

Fundació La Marató de TV3

Fundación Científica de la Asociación Española Contra el Cáncer

Publisher

Elsevier BV

Subject

Dermatology,Histology,Pathology and Forensic Medicine

Reference8 articles.

1. Digital imaging biomarkers feed machine learning for melanoma screening;Gareau;Exp Dermatol,2017

2. Deep-learning-based, computer-aided classifier developed with a small dataset of clinical images surpasses board-certified dermatologists in skin tumour diagnosis;Fujisawa;Br J Dermatol,2018

3. Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images;Marchetti;J Am Acad Dermatol,2018

4. The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions;Tschandl;Sci Data,2018

5. A state-of-the-art survey on lesion border detection in dermoscopy images;Celebi,2015

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2. Early Detection of Melanoma Using Convolutional Neural Network and Random Forest Algorithm;2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS);2023-03-17

3. Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application;Sensors;2022-10-17

4. Component Dimensionality Reduction in Dermoscopic Images using a Machine Learning Technique with Validation By Similarity Metrics;2022 IEEE 7th International conference for Convergence in Technology (I2CT);2022-04-07

5. Interpretability of a Deep Learning Based Approach for the Classification of Skin Lesions into Main Anatomic Body Sites;Cancers;2021-12-01