COMPREHENSIVE KNOWLEDGE-GUIDED ASSESSMENT OF SKIN LESIONBASED CANCER DETECTION

Skin cancer is considered as one of the scariest and most life-threatening forms of cancer. Unrepaireddeoxyribonucleic acid (DNA) in skin cells results in genetic flaws or mutations on the skin, which is the causeof skin cancer. Early detection of skin cancer symptoms is necessary due to the rising incidence of the disease,its high death rate, and the high cost of treatment. Additionally, because of artifacts, low contrast, and similarrepresentations like a mole, scar, etc., it can be difficult to distinguish skin cancer from a skin lesion.Therefore, techniques for lesion detection for accuracy, efficiency, and performance criteria are used toautomatically detect skin lesions. The aim of this systematic review is to analyze studies focused on skincancer image detection and classification. It also evaluates the effectiveness of these methods in real-worldclinical environments. So in this paper we carried out a thorough search of the literature from differentresearch papers only 15 papers that concentrated on creating, putting into practice, and validating methods toidentify, diagnose, and categorize skin cancer in clinical settings were examined and targeted by the search.Descriptive analysis, data scenarios, data processing and procedures, study findings and viewpoints, andphysician participation, diversity, and accessibility are all included in this review