RESUMO
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.
Assuntos
Dermatologia , Dermatopatias , Telemedicina , Adulto , Inteligência Artificial , Feminino , Humanos , Masculino , Redes Neurais de Computação , Estudos Prospectivos , Dermatopatias/diagnósticoRESUMO
We report a 68 years old man, farmer from the metropolitan region, admitted with a Hantavirus Cardiopulmonary Syndrome. The diagnosis was made using serologic test and was later confirmed by the Public Health Institute. He evolved to an early multiple organ failure, requiring high concentrations of oxygen and invasive ventilatory assistance, vasopressor drugs and renal replacement therapy. Swan Ganz and PiCCO were used simultaneously for hemodynamic monitoring. Treatment consisted in global support therapy, antimicrobial therapy and systemic corticosteroids. Intrathoracic blood volume was a more reliable parameter than pulmonary capillary wedge pressure for the assessment of preload. As expected in situations of increased vascular permeability, there was an increase in extravascular lung water. There was a good correlation between extravascular lung water and oxygenation parameters (PaO2/FiO2 and oxygenation index). PiCCO system may become a helpful tool in the management of patients with Hantavirus Cardiopulmonary Syndrome.