Skin Cancer Detection: A Review Using Deep Learning Techniques

Mehwish Dildar, Shumaila Akram, Muhammad Irfan, Hikmat Ullah Khan, Muhammad Ramzan, Abdur Rehman Mahmood, Soliman Ayed Alsaiari, Abdul Hakeem M Saeed, Mohammed Olaythah Alraddadi and Mater Hussen Mahnashi
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Mehwish Dildar: Government Associate College for Women Mari Sargodha, Sargodha 40100, Pakistan
Shumaila Akram: Department of Computer Science and Information Technology, University of Sargodha, Sargodha 40100, Pakistan
Muhammad Irfan: Electrical Engineering Department, College of Engineering, Najran University Saudi Arabia, Najran 61441, Saudi Arabia
Hikmat Ullah Khan: Department of Computer Science, Wah Campus, Comsats University, Wah Cantt 47040, Pakistan
Muhammad Ramzan: Department of Computer Science and Information Technology, University of Sargodha, Sargodha 40100, Pakistan
Abdur Rehman Mahmood: Department of Computer Science, COMSATS University Islamabad, Islamabad 440000, Pakistan
Soliman Ayed Alsaiari: Department of Internal Medicine, Faculty of Medicine, Najran University, Najran 61441, Saudi Arabia
Abdul Hakeem M Saeed: Department of Dermatology, Najran University Hospital, Najran 61441, Saudi Arabia
Mohammed Olaythah Alraddadi: Department of Internal Medicine, Faculty of Medicine, University of Tabuk, Tabuk 71491, Saudi Arabia
Mater Hussen Mahnashi: Department of Medicinal Chemistry, Pharmacy School, Najran University, Najran 61441, Saudi Arabia

IJERPH, 2021, vol. 18, issue 10, 1-22

Abstract: Skin cancer is one of the most dangerous forms of cancer. Skin cancer is caused by un-repaired deoxyribonucleic acid (DNA) in skin cells, which generate genetic defects or mutations on the skin. Skin cancer tends to gradually spread over other body parts, so it is more curable in initial stages, which is why it is best detected at early stages. The increasing rate of skin cancer cases, high mortality rate, and expensive medical treatment require that its symptoms be diagnosed early. Considering the seriousness of these issues, researchers have developed various early detection techniques for skin cancer. Lesion parameters such as symmetry, color, size, shape, etc. are used to detect skin cancer and to distinguish benign skin cancer from melanoma. This paper presents a detailed systematic review of deep learning techniques for the early detection of skin cancer. Research papers published in well-reputed journals, relevant to the topic of skin cancer diagnosis, were analyzed. Research findings are presented in tools, graphs, tables, techniques, and frameworks for better understanding.

Keywords: deep learning; deep neural network (DNN); machine learning; melanoma; support vector machine (SVM); skin lesion (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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