New Trends in Melanoma Detection Using Neural Networks: A Systematic Review.

Dan Popescu,Hassan El-Khatib,Loretta Ichim,Mohamed El-Khatib

doi:10.3390/s22020496

Dan Popescu, Hassan El-Khatib + Show 2 more

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https://doi.org/10.3390/s22020496

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Abstract

Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease today. The high mortality rate associated with melanoma makes it necessary to detect the early stages to be treated urgently and properly. This is the reason why many researchers in this domain wanted to obtain accurate computer-aided diagnosis systems to assist in the early detection and diagnosis of such diseases. The paper presents a systematic review of recent advances in an area of increased interest for cancer prediction, with a focus on a comparative perspective of melanoma detection using artificial intelligence, especially neural network-based systems. Such structures can be considered intelligent support systems for dermatologists. Theoretical and applied contributions were investigated in the new development trends of multiple neural network architecture, based on decision fusion. The most representative articles covering the area of melanoma detection based on neural networks, published in journals and impact conferences, were investigated between 2015 and 2021, focusing on the interval 2018–2021 as new trends. Additionally presented are the main databases and trends in their use in teaching neural networks to detect melanomas. Finally, a research agenda was highlighted to advance the field towards the new trends.

Highlights

Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania; Abstract: Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease today
Sun X. et al [4] the main cause of Me occurrence is exposure to ultraviolet radiation. Due to this excessive exposure, some mutations that occur at the level of melanocytes can lead to Me genesis. Even though it is one of the deadliest types of skin cancers, many studies showed that early detection of Me leads to its treatment in 90% of cases [5]
As we considered the new trends in Me detection using neural network-based methods (NNs), we searched the following DSs: Web of Science, Scopus, and PubMed between 2015 and 2021 considering the following topics: melanoma, skin lesions, artificial intelligence, machine learning, deep learning, and convolutional neural networks

Summary

Introduction

Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania; Abstract: Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease today. The paper presents a systematic review of recent advances in an area of increased interest for cancer prediction, with a focus on a comparative perspective of melanoma detection using artificial intelligence, especially neural network-based systems. Such structures can be considered intelligent support systems for dermatologists. A lot of researchers have put their ideas together to try to develop an automatic Me detection system based on machine learning (ML) that provides a quick result with high ACC, even if the complexity of skin lesion (SL) images analysis presented many problems [12,13]. It is a rather complex task to find a suitable diagnosis algorithm due to the presence of artifacts, such as the presence of hair around or even in Academic Editor: Ludovic Macaire

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