Artificial intelligence in the detection of skin cancer

被引:22
|
作者
Beltrami, Eric J. [1 ]
Brown, Alistair C. [2 ]
Salmon, Paul J. M. [2 ]
Leffell, David J. [3 ]
Ko, Justin M. [4 ]
Grant-Kels, Jane M. [5 ,6 ]
机构
[1] Univ Connecticut, Sch Med, Farmington, CT USA
[2] SkinCentre, Dermatol Surg Unit, Wellington, New Zealand
[3] Yale Sch Med, Dept Dermatol, New Haven, CT USA
[4] Stanford Med, Dept Dermatol, Stanford, CA USA
[5] Univ Connecticut, Dept Dermatol, Sch Med, 21 South Rd, Farmington, CT 06032 USA
[6] Univ Florida, Coll Med, Gainesville, FL USA
关键词
artificial intelligence; clinical practice; diagnosis; health care dollars; machine learning; neural networks; skin cancer; technology;
D O I
10.1016/j.jaad.2022.08.028
中图分类号
R75 [皮肤病学与性病学];
学科分类号
100206 ;
摘要
Recent advances in artificial intelligence (AI) in dermatology have demonstrated the potential to improve the accuracy of skin cancer detection. These capabilities may augment current diagnostic processes and improve the approach to the management of skin cancer. To explain this technology, we discuss fundamental terminology, potential benefits, and limitations of AI, and commercial applications relevant to dermatologists. A clear understanding of the technology may help to reduce physician concerns about AI and promote its use in the clinical setting. Ultimately, the development and validation of AI technologies, their approval by regulatory agencies, and widespread adoption by dermatologists and other clinicians may enhance patient care. Technology-augmented detection of skin cancer has the potential to improve quality of life, reduce health care costs by reducing unnecessary procedures, and promote greater access to high-quality skin assessment. Dermatologists play a critical role in the responsible development and deployment of AI capabilities applied to skin cancer.
引用
收藏
页码:1336 / 1342
页数:7
相关论文
共 50 条
  • [31] Role of Artificial Intelligence and Deep Learning in Easier Skin Cancer Detection through Antioxidants Present in Food
    Sreevidya, R. C. R.
    Jalaja, G.
    Sajitha, N.
    Padmaja, D. Lakshmi
    Nagaprasad, S.
    Pant, Kumud
    Kumar, Yekula Prasanna
    JOURNAL OF FOOD QUALITY, 2022, 2022
  • [32] Artificial intelligence and improved early detection for pancreatic cancer
    Zhong, Jun
    Shi, Jianxin
    Amundadottir, Laufey T.
    INNOVATION, 2023, 4 (04):
  • [33] Artificial intelligence technique in detection of early esophageal cancer
    Lu-Ming Huang
    Wen-Juan Yang
    Zhi-Yin Huang
    Cheng-Wei Tang
    Jing Li
    World Journal of Gastroenterology, 2020, 26 (39) : 5959 - 5969
  • [34] Development of artificial intelligence for the detection and staging of esophageal cancer
    Tokai, Yoshitaka
    Yoshio, Toshiyuki
    Fujisaki, Junko
    ANNALS OF ESOPHAGUS, 2023, 6
  • [35] The evolving landscape: Role of artificial intelligence in cancer detection
    Kumar, Praveen
    Izankar, Sakshi V.
    Weerarathna, Induni N.
    Raymond, David
    Verma, Prateek
    AIMS BIOENGINEERING, 2024, 11 (02): : 147 - 172
  • [36] Artificial intelligence technique in detection of early esophageal cancer
    Huang, Lu-Ming
    Yang, Wen-Juan
    Huang, Zhi-Yin
    Tang, Cheng-Wei
    Li, Jing
    WORLD JOURNAL OF GASTROENTEROLOGY, 2020, 26 (39) : 5959 - 5969
  • [37] Recent Applications of Artificial Intelligence in Early Cancer Detection
    Khanam, Nausheen
    Kumar, Rajnish
    CURRENT MEDICINAL CHEMISTRY, 2022, 29 (25) : 4410 - 4435
  • [38] Artificial intelligence for cancer detection of the upper gastrointestinal tract
    Suzuki, Hideo
    Yoshitaka, Tokai
    Yoshio, Toshiyuki
    Tada, Tomohiro
    DIGESTIVE ENDOSCOPY, 2021, 33 (02) : 254 - 262
  • [39] Artificial intelligence in skin of color
    Abrouk, Michael
    Egger, Andjela
    Brodsky, Merrick
    Krishnan, Srikanth
    Desai, Karishma
    Nouri, Keyvan
    JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY, 2020, 83 (06) : AB215 - AB215
  • [40] Mapping the landscape of artificial intelligence in skin cancer research: a bibliometric analysis
    Liu, Qianwei
    Zhang, Jie
    Bai, Yanping
    FRONTIERS IN ONCOLOGY, 2023, 13