An artificial intelligence based app for skin cancer detection evaluated in a population based setting

被引:0
|
作者
Anna M. Smak Gregoor
Tobias E. Sangers
Lytske J. Bakker
Loes Hollestein
Carin A. Uyl – de Groot
Tamar Nijsten
Marlies Wakkee
机构
[1] University Medical Center Rotterdam,Department of Dermatology, Erasmus MC Cancer Institute
[2] Erasmus University Rotterdam,Erasmus School of Health Policy & Management
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Artificial intelligence (AI) based algorithms for classification of suspicious skin lesions have been implemented in mobile phone apps (mHealth), but their effect on healthcare systems is undocumented. In 2019, a large Dutch health insurance company offered 2.2 million adults free access to an mHealth app for skin cancer detection. To study the impact on dermatological healthcare consumption, we conducted a retrospective population-based pragmatic study. We matched 18,960 mHealth-users who completed at least one successful assessment with the app to 56,880 controls who did not use the app and calculated odds ratios (OR) to compare dermatological claims between both groups in the first year after granting free access. A short-term cost-effectiveness analysis was performed to determine the cost per additional detected (pre)malignancy. Here we report that mHealth-users had more claims for (pre)malignant skin lesions than controls (6.0% vs 4.6%, OR 1.3 (95% CI 1.2–1.4)) and also a more than threefold higher risk of claims for benign skin tumors and nevi (5.9% vs 1.7%, OR 3.7 (95% CI 3.4–4.1)). The costs of detecting one additional (pre)malignant skin lesion with the app compared to the current standard of care were €2567. Based on these results, AI in mHealth appears to have a positive impact on detecting more cutaneous (pre)malignancies, but this should be balanced against the for now stronger increase in care consumption for benign skin tumors and nevi.
引用
下载
收藏
相关论文
共 50 条
  • [1] An artificial intelligence based app for skin cancer detection evaluated in a population based setting
    Gregoor, Anna M. Smak M.
    Sangers, Tobias E.
    Bakker, Lytske J.
    Hollestein, Loes
    Uyl-de Groot, Carin A. A.
    Nijsten, Tamar
    Wakkee, Marlies
    NPJ DIGITAL MEDICINE, 2023, 6 (01)
  • [2] Artificial intelligence in the detection of skin cancer
    Beltrami, Eric J.
    Brown, Alistair C.
    Salmon, Paul J. M.
    Leffell, David J.
    Ko, Justin M.
    Grant-Kels, Jane M.
    JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY, 2022, 87 (06) : 1336 - 1342
  • [3] Artificial intelligence-based classification for the diagnostics of skin cancer
    Winkler, Julia K.
    Haenssle, Holger A.
    DERMATOLOGIE, 2022, 73 (11): : 838 - 844
  • [4] Artificial Intelligence for Skin Cancer Detection: Scoping Review
    Takiddin, Abdulrahman
    Schneider, Jens
    Yang, Yin
    Abd-Alrazaq, Alaa
    Househ, Mowafa
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 23 (11)
  • [5] Artificial intelligence in the detection of skin cancer: State of the art
    Strzelecki, Michal
    Kociolek, Marcin
    Strakowska, Maria
    Kozlowski, Michal
    Grzybowski, Andrzej
    Szczypinski, Piotr M.
    CLINICS IN DERMATOLOGY, 2024, 42 (03) : 280 - 295
  • [6] Artificial Intelligence-Based Skin Cancer Phone Apps Unreliable
    Abbasi, Jennifer
    JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2020, 323 (14): : 1336 - 1336
  • [7] Early Detection of Lung Cancer based on Artificial Intelligence Techniques
    Taher, Fatma
    2017 INTERNATIONAL CONFERENCE ON INFOCOM TECHNOLOGIES AND UNMANNED SYSTEMS (TRENDS AND FUTURE DIRECTIONS) (ICTUS), 2017, : 114 - 114
  • [8] Artificial intelligence (AI) for breast cancer screening: BreastScreen population-based cohort study of cancer detection
    Marinovich, M. Luke
    Wylie, Elizabeth
    Lotter, William
    Lund, Helen
    Waddell, Andrew
    Madeley, Carolyn
    Pereira, Gavin
    Houssami, Nehmat
    EBIOMEDICINE, 2023, 90
  • [9] Optimal Artificial Intelligence Based Automated Skin Lesion Detection and Classification Model
    Ogudo, Kingsley A.
    Surendran, R.
    Khalaf, Osamah Ibrahim
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2023, 44 (01): : 693 - 707
  • [10] Artificial intelligence and skin cancer
    Wei, Maria L.
    Tada, Mikio
    So, Alexandra
    Torres, Rodrigo
    FRONTIERS IN MEDICINE, 2024, 11