Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Diagnostic capacity of skin tumor artificial intelligence-assisted decision-making software in real-world clinical settings
Chengxu Li, Wenmin Fei, Changbing Shen, et al.
Chinese Medical Journal (2020) Vol. 133, Iss. 17, pp. 2020-2026
Open Access | Times Cited: 17

Showing 17 citing articles:

Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms
Roxana Daneshjou, Mary P. Smith, Mary Sun, et al.
JAMA Dermatology (2021) Vol. 157, Iss. 11, pp. 1362-1362
Open Access | Times Cited: 195
A systematic review and meta-analysis of artificial intelligence versus clinicians for skin cancer diagnosis
María Paz Salinas, Javiera Sepúlveda, Leonel Hidalgo, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 17
Accuracy of an artificial intelligence as a medical device as part of a UK-based skin cancer teledermatology service
Helen Marsden, Polychronis Kemos, Marcello Venzi, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 7
Artificial Intelligence for the Classification of Pigmented Skin Lesions in Populations with Skin of Color: A Systematic Review
Yuyang Liu, Clare A. Primiero, Vishnutheertha Kulkarni, et al.
Dermatology (2023) Vol. 239, Iss. 4, pp. 499-513
Open Access | Times Cited: 20
Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance
Lucy Thomas, Chris Hyde, Daniel Mullarkey, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 14
Artificial Intelligence Applied to Non-Invasive Imaging Modalities in Identification of Nonmelanoma Skin Cancer: A Systematic Review
Emilie A. Foltz, Alexander Witkowski, Alyssa L. Becker, et al.
Cancers (2024) Vol. 16, Iss. 3, pp. 629-629
Open Access | Times Cited: 4
Performance of Commercial Dermatoscopic Systems That Incorporate Artificial Intelligence for the Identification of Melanoma in General Practice: A Systematic Review
Ian Miller, Nedeljka Rosić, Michael Stapelberg, et al.
Cancers (2024) Vol. 16, Iss. 7, pp. 1443-1443
Open Access | Times Cited: 4
Deep learning algorithms for melanoma detection using dermoscopic imaging: A systematic review and meta-analysis
Zichen Ye, Daqian Zhang, Yuankai Zhao, et al.
Artificial Intelligence in Medicine (2024) Vol. 155, pp. 102934-102934
Closed Access | Times Cited: 4
An Intelligent Diagnostic Model for Melasma Based on Deep Learning and Multimode Image Input
Lin Liu, Liang Chen, Yuzhou Xue, et al.
Dermatology and Therapy (2022) Vol. 13, Iss. 2, pp. 569-579
Open Access | Times Cited: 15
Effectiveness of an image analyzing AI-based Digital Health Technology to identify Non-Melanoma Skin Cancer and other skin lesions: results of the DERM-003 study
Helen Marsden, Caroline Morgan, Stephanie Austin, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 8
Determining the clinical applicability of machine learning models through assessment of reporting across skin phototypes and rarer skin cancer types: A systematic review
Lloyd Steele, Xiang Li Tan, Bayanne Olabi, et al.
Journal of the European Academy of Dermatology and Venereology (2022) Vol. 37, Iss. 4, pp. 657-665
Open Access | Times Cited: 8
Artificial Intelligence in Cutaneous Lesions: Where do we Stand and What is Next?
Mara Giavina‐Bianchi, Justin Ko, Mara Giavina, et al.
Frontiers research topics (2024)
Open Access | Times Cited: 1
Construction of an artificial intelligence system in dermatology: effectiveness and consideration of Chinese Skin Image Database (CSID)
Chengxu Li, Wenmin Fei, Yang Han, et al.
Intelligent Medicine (2021) Vol. 1, Iss. 2, pp. 56-60
Open Access | Times Cited: 7
Artificial Intelligence Assistive Technology in Hospital Professional Nursing Technology
Yanxue Cai, Moorhe Clinto, Zhangbo Xiao
Journal of Healthcare Engineering (2021) Vol. 2021, pp. 1-7
Open Access | Times Cited: 5
AI-Powered Computer Vision for Early Skin Cancer Detection with IoT-Connected Dermascopes
K Ravindar, Eswararao Boddepalli, Atul Singla, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 1
Editorial: Progress and Prospects on Skin Imaging Technology, Teledermatology and Artificial Intelligence in Dermatology
Chengxu Li, Je‐Ho Mun, Paola Pasquali, et al.
Frontiers in Medicine (2021) Vol. 8
Open Access | Times Cited: 2
Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance
Dilraj Kalsi, Lucy Thomas, Chris Hyde, et al.
Research Square (Research Square) (2023)
Open Access
Page 1

Scroll to top