This paper is in the following e-collection/theme issue:

Artificial Intelligence (1197) Digital Photography and Imaging in Dermatology (31) Image Recognition and AI in Dermatology (9) Machine Learning from Digital Images in Dermatology (8) Skin Cancer and Melanoma Prevention (110) Reviews in Dermatology (33) Digital Health Reviews (1186)

Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22934, first published .
Artificial Intelligence for Skin Cancer Detection: Scoping Review

Artificial Intelligence for Skin Cancer Detection: Scoping Review

Artificial Intelligence for Skin Cancer Detection: Scoping Review

Authors of this article:

Abdulrahman Takiddin1, 2 Author Orcid Image ;   Jens Schneider2 Author Orcid Image ;   Yin Yang2 Author Orcid Image ;   Alaa Abd-Alrazaq2 Author Orcid Image ;   Mowafa Househ2 Author Orcid Image
Article Authors Cited by (29) Tweetations (7) Metrics

Journals

  1. Zhou Y, Shi Y, Lu W, Wan F. Did Artificial Intelligence Invade Humans? The Study on the Mechanism of Patients’ Willingness to Accept Artificial Intelligence Medical Care: From the Perspective of Intergroup Threat Theory. Frontiers in Psychology 2022;13 View
  2. Soglia S, Pérez-Anker J, Lobos Guede N, Giavedoni P, Puig S, Malvehy J. Diagnostics Using Non-Invasive Technologies in Dermatological Oncology. Cancers 2022;14(23):5886 View
  3. Na Takuathung M, Klinjan P, Sakuludomkan W, Dukaew N, Inpan R, Kongta R, Chaiyana W, Teekachunhatean S, Koonrungsesomboon N. Efficacy and Safety of the Genistein Nutraceutical Product Containing Vitamin E, Vitamin B3, and Ceramide on Skin Health in Postmenopausal Women: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial. Journal of Clinical Medicine 2023;12(4):1326 View
  4. Sanchez K, Kamal K, Manjaly P, Ly S, Mostaghimi A. Clinical Application of Artificial Intelligence for Non-melanoma Skin Cancer. Current Treatment Options in Oncology 2023;24(4):373 View
  5. Deniz-Garcia A, Fabelo H, Rodriguez-Almeida A, Zamora-Zamorano G, Castro-Fernandez M, Alberiche Ruano M, Solvoll T, Granja C, Schopf T, Callico G, Soguero-Ruiz C, Wägner A. Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges. Journal of Medical Internet Research 2023;25:e44030 View
  6. Goyal R, Husain S, Wilson K, Chopra H, Pahwa R, Loganathan M, Sharma R. Recent advancements in skin cancer treatment: a critical review. Exploration of Medicine 2023:782 View
  7. Messaoudi H, Belaid A, Ben Salem D, Conze P. Cross-dimensional transfer learning in medical image segmentation with deep learning. Medical Image Analysis 2023;88:102868 View
  8. Knoedler L, Knoedler S, Allam O, Remy K, Miragall M, Safi A, Alfertshofer M, Pomahac B, Kauke-Navarro M. Application possibilities of artificial intelligence in facial vascularized composite allotransplantation—a narrative review. Frontiers in Surgery 2023;10 View
  9. Kuo K, Talley P, Chang C. The accuracy of artificial intelligence used for non-melanoma skin cancer diagnoses: a meta-analysis. BMC Medical Informatics and Decision Making 2023;23(1) View
  10. Liu Y, Primiero C, Kulkarni V, Soyer H, Betz-Stablein B. Artificial Intelligence for the Classification of Pigmented Skin Lesions in Populations with Skin of Color: A Systematic Review. Dermatology 2023;239(4):499 View
  11. Park H, Park S, Lee S, Hwang J, Lee M, Jang S, Jung Y, Yeon Y, Kang N, Suh B, Kim E. Development and application of artificial intelligence‐based facial skin image diagnosis system: Changes in facial skin characteristics with ageing in Korean women. International Journal of Cosmetic Science 2024;46(2):199 View
  12. Fazakarley C, Breen M, Leeson P, Thompson B, Williamson V. Experiences of using artificial intelligence in healthcare: a qualitative study of UK clinician and key stakeholder perspectives. BMJ Open 2023;13(12):e076950 View
  13. Rokhshad R, Mohammad-Rahimi H, Price J, Shoorgashti R, Abbasiparashkouh Z, Esmaeili M, Sarfaraz B, Rokhshad A, Motamedian S, Soltani P, Schwendicke F. Artificial intelligence for classification and detection of oral mucosa lesions on photographs: a systematic review and meta-analysis. Clinical Oral Investigations 2024;28(1) View
  14. Foltz E, Witkowski A, Becker A, Latour E, Lim J, Hamilton A, Ludzik J. Artificial Intelligence Applied to Non-Invasive Imaging Modalities in Identification of Nonmelanoma Skin Cancer: A Systematic Review. Cancers 2024;16(3):629 View
  15. Fazakarley C, Breen M, Thompson B, Leeson P, Williamson V. Beliefs, experiences and concerns of using artificial intelligence in healthcare: A qualitative synthesis. DIGITAL HEALTH 2024;10 View
  16. Myslicka M, Kawala-Sterniuk A, Bryniarska A, Sudol A, Podpora M, Gasz R, Martinek R, Kahankova Vilimkova R, Vilimek D, Pelc M, Mikolajewski D. Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes. Archives of Dermatological Research 2024;316(4) View
  17. Thanga Purni J, Vedhapriyavadhana R. EOSA-Net: A deep learning framework for enhanced multi-class skin cancer classification using optimized convolutional neural networks. Journal of King Saud University - Computer and Information Sciences 2024;36(3):102007 View
  18. Fu Q, Gao H, Liu K, Su J, Zhang J, Guo X, Yang F. Identification of circRNA-miRNA-mRNA Network Regulated by Hsp90 in Human Melanoma A375 Cells. Combinatorial Chemistry & High Throughput Screening 2024;27(2):307 View
  19. Tamrat T, Zhao Y, Schalet D, AlSalamah S, Pujari S, Say L. Exploring the Use and Implications of AI in Sexual and Reproductive Health and Rights: Protocol for a Scoping Review. JMIR Research Protocols 2024;13:e53888 View
  20. K. A, T.Y. S, Ahmed S, Mathivanan S, Varadhan S, Shah M. Trained neural networking framework based skin cancer diagnosis and categorization using grey wolf optimization. Scientific Reports 2024;14(1) View
  21. Almufareh M. Unveiling the Spectrum of UV-Induced DNA Damage in Melanoma: Insights From AI-Based Analysis of Environmental Factors, Repair Mechanisms, and Skin Pigment Interactions. IEEE Access 2024;12:64837 View
  22. Salinas M, Sepúlveda J, Hidalgo L, Peirano D, Morel M, Uribe P, Rotemberg V, Briones J, Mery D, Navarrete-Dechent C. A systematic review and meta-analysis of artificial intelligence versus clinicians for skin cancer diagnosis. npj Digital Medicine 2024;7(1) View
  23. Semerci Z, Toru H, Çobankent Aytekin E, Tercanlı H, Chiorean D, Albayrak Y, Cotoi O. The Role of Artificial Intelligence in Early Diagnosis and Molecular Classification of Head and Neck Skin Cancers: A Multidisciplinary Approach. Diagnostics 2024;14(14):1477 View

Books/Policy Documents

  1. Završnik A. Artificial Intelligence, Social Harms and Human Rights. View
  2. de Lima L, Krohling R. Intelligent Systems. View
  3. Dhiman A, Chauhan N. Proceedings of the International Health Informatics Conference. View