Performance of a deep neural network in teledermatology: a single-centre prospective diagnostic study.

BACKGROUND: The use of artificial intelligence (AI) algorithms for the diagnosis of skin diseases has shown promise in experimental settings but has not been yet tested in real-life conditions. OBJECTIVE: To assess the diagnostic performance and potential clinical utility of a 174-multiclass AI algorithm in a real-life telemedicine setting. METHODS: Prospective, diagnostic accuracy study including consecutive patients who submitted images for teledermatology evaluation. The treating dermatologist chose a single image to upload to a web application during teleconsultation. A follow-up reader study including nine healthcare providers (3 dermatologists, 3 dermatology residents and 3 general practitioners) was performed. RESULTS: A total of 340 cases from 281 patients met study inclusion criteria. The mean (SD) age of patients was 33.7 (17.5) years; 63% (n = 177) were female. Exposure to the AI algorithm results was considered useful in 11.8% of visits (n = 40) and the teledermatologist correctly modified the real-time diagnosis in 0.6% (n = 2) of cases. The overall top-1 accuracy of the algorithm (41.2%) was lower than that of the dermatologists (60.1%), residents (57.8%) and general practitioners (49.3%) (all comparisons P < 0.05, in the reader study). When the analysis was limited to the diagnoses on which the algorithm had been explicitly trained, the balanced top-1 accuracy of the algorithm (47.6%) was comparable to the dermatologists (49.7%) and residents (47.7%) but superior to the general practitioners (39.7%; P = 0.049). Algorithm performance was associated with patient skin type and image quality. CONCLUSIONS: A 174-disease class AI algorithm appears to be a promising tool in the triage and evaluation of lesions with patient-taken photographs via telemedicine.

Cutaneous manifestations in renal transplant recipients of Santiago, Chile.

INTRODUCTION: Renal transplant recipients have a heightened risk of developing various cutaneous manifestations, such as skin infections, skin cancer, and secondary effects of immunosuppressive drugs. These manifestations differ depending on the evaluated population. The objective of this study was to describe the prevalence of cutaneous manifestations among renal transplant recipients in Chile between 1979 and 2008. METHODS: Patients were recruited and then evaluated using a standardized questionnaire. Dermatologic physical examination was performed in every patient describing skin lesions, immunosuppressive drug effects, and malignant diseases. All suspicious lesions were biopsied for analysis. Every patient was queried for the development of skin cancer after his or her transplantation. RESULTS: A total of 91 patients were enrolled; ages 10-67 years. Sixty percent of the patients presented with an infection at the initial evaluation. The most common infection was onychomycosis (58%) and verruca vulgaris (25%). In this study 58% of patients developed cutaneous side effects of immunosuppressive drugs. Among the evaluated patients, 16% showed premalignant or malignant manifestations on physical examination. The most frequent manifestations were actinic keratosis (17%), basal cell carcinoma (1%), and squamous cell carcinoma (1%). On a retrospective analysis, 12% of patients developed skin cancer after transplantation, 66% squamous cell carcinoma and 34% basal cell carcinoma, with a ratio of 1.9 to 1. DISCUSSION: Cutaneous manifestations in renal transplant recipients are generally secondary to immunosuppression. These patients show a greater risk of having human papilloma virus (HPV) infections and nonmelanoma skin cancer. Periodic dermatologic evaluation of these patients should be performed to detect early lesions and modify risk factors.