Article
Reimagining leprosy elimination with AI analysis of a combination of skin lesion images with demographic and clinical data
Registro en:
BARBIERI, Raquel R. et al. Reimagining leprosy elimination with AI analysis of a combination of skin lesion images with demographic and clinical data. The Lancet, v. 9, p. 1-9, May 2022.
0140-6736
10.1016/j.lana.2022.100192
Autor
Barbieri, Raquel R.
Yixi, Xu
Setian, Lucy
Souza-Santos, Paulo Thiago
Trivedi, Anusua
Cristofono, Jim
Bhering, Ricardo
White, Kevin
Sales, Anna M.
Miller, Geralyn
Nery, José Augusto C.
Sharman, Michael
Bumann, Richard
Shun, Zhang
Goldust, Mohamad
Sarno, Euzenir N.
Mirza, Fareed
Cavaliero, Arielle
Timmer, Sander
Bonfiglioli, Elena
Smith, Cairns
Scollard, David
Navarini, Alexander A.
Aerts, Ann
Ferres, Juan Lavista
Moraes, Milton O.
Resumen
Leprosy is an infectious disease that mostly affects underserved populations. Although it has been
largely eliminated, still about 200’000 new patients are diagnosed annually. In the absence of a diagnostic test, clin-
ical diagnosis is often delayed, potentially leading to irreversible neurological damage and its resulting stigma, as
well as continued transmission. Accelerating diagnosis could significantly contribute to advancing global leprosy
elimination. Digital and Artificial Intelligence (AI) driven technology has shown potential to augment health work-
ers abilities in making faster and more accurate diagnosis, especially when using images such as in the fields of der-
matology or ophthalmology. That made us start the quest for an AI-driven diagnosis assistant for leprosy, based on
skin images.