Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review

Skin cancers occur commonly worldwide. The prognosis and disease burden are highly dependent on the cancer type and disease stage at diagnosis. We systematically reviewed studies on artificial intelligence and machine learning (AI/ML) algorithms that aim to facilitate the early diagnosis of skin cancers, focusing on their application in primary and community care settings. We searched MEDLINE, Embase, Scopus, and Web of Science (from Jan 1, 2000, to Aug 9, 2021) for all studies providing evidence on applying AI/ML algorithms to the early diagnosis of skin cancer, including all study designs and languages. The primary outcome was diagnostic accuracy of the algorithms for skin cancers. The secondary outcomes…

• BC
  Baylor College of Medicine
• CR
  Cancer Research UK

  Awards: A23385, C8640/A23385, C8640
• NI
  National Institute for Health and Care Research

  Awards: PRU-1217-21601, C8640/A23385, PR-PRU-1217–21601, PR-PRU-1217-21601
• DO
  Department of Health and Social Care
• UO
  University of Exeter
• MR
  Medical Research Council
• NH
  National Health and Medical Research Council

  Award: APP1195302