Accuracy of an artificial intelligence as a medical device as part of a UK-based skin cancer teledermatology service.

ABSTRACT:

Introduction

An artificial intelligence as a medical device (AIaMD), built on convolutional neural networks, has demonstrated high sensitivity for melanoma. To be of clinical value, it needs to safely reduce referral rates. The primary objective of this study was to demonstrate that the AIaMD had a higher rate of correctly classifying lesions that did not need to be referred for biopsy or urgent face-to-face dermatologist review, compared to teledermatology standard of care (SoC), while achieving the same sensitivity to detect malignancy. Secondary endpoints included the sensitivity, specificity, positive and negative predictive values, and number needed to biopsy to identify one case of melanoma or squamous cell carcinoma (SCC) by both the AIaMD and SoC.

Methods

This prospe

SUBMITTER: Marsden H 

PROVIDER: S-EPMC10996444 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature