Comprehensive Summary
With the acceleration of telemedicine during the COVID-19 pandemic, there was a growing concern about helping patients with various skin conditions. Limited or poor-quality skin lesion images often disrupted clinical care, preventing clinicians from meeting diagnostic standards. Artificial intelligence (AI) was found to potentially address this issue by improving image quality, which this study investigated in a telemedicine setting. Adults aged 18 and older with skin conditions were enrolled and provided with a smartphone equipped with an AI algorithm that guided them to take up to four photos of their skin, selecting the best image for the telemedicine provider. Results of the study showed that the AI algorithm reduced the number of patients submitting poor-quality images by 68%. Additionally, across all participants, it significantly improved overall photo quality, leading to easier identification of skin lesions and more accurate clinical diagnoses. This demonstrates that AI algorithms can effectively identify and enhance insufficient-quality images for clinical use.
Outcomes and Implications
The use of AI algorithms represents a major advancement for telemedicine by simplifying the process for both clinicians and patients. With improved communication and image quality, more personalized and accurate care can be delivered from the comfort of a patient’s home. This enhancement could increase trust and adoption of telemedicine, offering greater flexibility for patients while reducing clinician workload. Moreover, this study provides insight into how AI can streamline clinical workflows and highlights its potential applications across other areas of medicine.