Comparing the number-needed-to-biopsy ratio for melanoma diagnosis by artificial intelligence as a medical device, teledermatology and face-to-face models of care
To the best of our knowledge, this is the first UK study to compare the number-needed-to-biopsy (NNB) ratio for melanoma diagnosis across three different models of care, incorporating artificial intelligence as a medical device (AIaMD) alongside teledermatology. We present encouraging results from our centre, with NNB ratios that are comparable among all three models and lower than the average NNB ratio reported in a worldwide meta-analysis. We highlight the use of AIaMD in the correct identification of benign lesions and encourage further work to improve and validate performance, thereby maintaining patient safety. Finally, we consider a hybrid model as a potential strategy to streamline current pathways and address the increasing demands on urgent skin cancer services.
Authors
- Louise A. Fearfield (ORCID: https://orcid.org/0000-0002-1122-4216)
- Radhika Bali (ORCID: https://orcid.org/0000-0002-1211-6217)
- Khawar Hussain (ORCID: https://orcid.org/0000-0003-2116-7718)
- Jenny G Chung (ORCID: https://orcid.org/0000-0001-9756-466X)
- Lucy Thomas
Institutions
- Chelsea and Westminster Hospital NHS Foundation Trust (GB)
Publication Details
- Journal
- Clinical and Experimental Dermatology
- Published
- 2025-03-11
- DOI
- https://doi.org/10.1093/ced/llaf120
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00