Abstract
Recent studies show promising potential for artificial intelligence (AI) to assist healthcare providers (HCPs) in skin cancer care. The aim of this study is to explore the views of dermatologists and general practitioners (GPs) regarding the successful implementation of AI when assisting HCPs in skin cancer care. We performed a qualitative focus group study, consisting of six focus groups with 16 dermatologists and 17 GPs, varying in prior knowledge and experience with AI, gender, and age. An in-depth inductive thematic content analysis was deployed. Perceived benefits, barriers, and preconditions were identified as main themes. Dermatologists and GPs perceive substantial benefits of AI, particularly an improved health outcome and care pathway between primary and secondary care. Doubts about accuracy, risk of health inequalities, and fear of replacement were among the most stressed barriers. Essential preconditions included adequate algorithm content, sufficient usability, and accessibility of AI. In conclusion, dermatologists and GPs perceive significant benefits from implementing AI in skin cancer care. However, to successfully implement AI, key barriers need to be addressed. Efforts should focus on ensuring algorithm transparency, validation, accessibility for all skin types, and adequate regulation of algorithms. Simultaneously, improving knowledge about AI could reduce the fear of replacement.
| Original language | English |
|---|---|
| Pages (from-to) | 1187-1195 |
| Number of pages | 9 |
| Journal | Archives of Dermatological Research |
| Volume | 315 |
| Issue number | 5 |
| Early online date | 7 Dec 2022 |
| DOIs | |
| Publication status | Published - Jul 2023 |
Bibliographical note
Funding Information: This study was initiated by the Erasmus MC Cancer Institute and was supported by an unrestricted research grant from SkinVision. SkinVision was not involved in the design of the study, data collection, data analysis, manuscript preparation or in the decision to publish this study.Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
