###### Abstract  
Skin cancer (SC) is one of the most prevalent cancers worldwide. Clinical evaluation of skin lesions is necessary to assess the characteristics of the disease; however, it is limited by long timelines and variety in interpretation. As early and accurate diagnosis of SC is crucial to increase patient survival rates, machine-learning (ML) and deep-learning (DL) approaches have been developed to overcome these issues and support dermatologists. We present a systematic literature review of recent research on the use of machine learning to classify skin lesions with the aim of providing a solid starting point for researchers beginning to work in this area. A search was conducted in several electronic databases by applying inclusion/exclusion filters and for this review, only those documents that clearly and completely described the procedures performed and reported the results obtained were selected. Sixty-eight articles were selected, of which the majority use DL approaches, in particular convolutional neural networks (CNN), while a smaller portion rely on ML techniques or hybrid ML/DL approaches for skin cancer detection and classification. Many ML and DL methods show high performance as classifiers of skin lesions. The promising results obtained to date bode well for the not-too-distant inclusion of these techniques in clinical practice. skin cancer; skin lesion classification; melanoma classification; computer-aided diagnostics; artificial intelligence; machine learning; deep learning; convolutional neural networks +
Footnote †: journal:  
11 October 2022  
Accepted: 17 November 2022  
Published: 21 November 2022  
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**1. Introduction**  
Skin cancer is among the most common types of cancer in the Caucasian population worldwide [1]. It is one of the three most dangerous and fastest-growing types of cancer and therefore represents a significant public health problem [2]. According to the World Health Organisation, one out of every three cancer diagnoses is related to skin cancer [3] and according to the Skin Cancer Foundation, the global incidence of skin cancer continues to increase [4]. Skin tumours can be either benign or malignant; both types originate from DNA [5] damage due to ultraviolet radiation exposure that causes uncontrolled cell proliferation. Benign tumours, although they grow, do not spread. These include seborrhoeic keratosis, cherry angiomas, dermatofibroma, skin tags, pyrogenic granuloma, and cysts [6]. In contrast, malignant tumours expand in the patient's body, spread uncontrollably, and can infiltrate other tissues/organs. Below are the most frequent forms of cutaneous malignant tumours [7, 8]. **Basal cell carcinoma or basalioma (BCC) (Figure 0(a)). It accounts for about 80% of cases and originates in the basal cells, the deepest cells of the epidermis. Basal cell growth is slow, so in most cases BCC is curable and causes minimal damage if diagnosed and treated in time. **Squamous cell carcinoma or cutaneous spinocellular carcinoma (SCC) (Figure 1b). This accounts for approximately 16% of skin cancers and originates in the squamous cells in the most superficial layer of the epidermis. If detected early it is easily curable, but if neglected it can infiltrate the deeper layers of the skin and spread to other parts of the body. **Malignant Melanoma (MM)** (Figure 1c). Originating in the melanocytic cells located in the epidermis, it is the most aggressive malignant skin tumour. It spreads rapidly, has a high mortality rate as it metastasises in the early stages, and is difficult to treat. It accounts for only 4% of skin cancers but induces mortality in 80% of cases. Only 14% of patients with metastatic melanoma survive for five years [9]. If diagnosed in the early stages it has a 95% curability rate, so its early diagnosis can greatly increase life chances.