dc.creator | Barbieri, Raquel R. | |
dc.creator | Yixi, Xu | |
dc.creator | Setian, Lucy | |
dc.creator | Souza-Santos, Paulo Thiago | |
dc.creator | Trivedi, Anusua | |
dc.creator | Cristofono, Jim | |
dc.creator | Bhering, Ricardo | |
dc.creator | White, Kevin | |
dc.creator | Sales, Anna M. | |
dc.creator | Miller, Geralyn | |
dc.creator | Nery, José Augusto C. | |
dc.creator | Sharman, Michael | |
dc.creator | Bumann, Richard | |
dc.creator | Shun, Zhang | |
dc.creator | Goldust, Mohamad | |
dc.creator | Sarno, Euzenir N. | |
dc.creator | Mirza, Fareed | |
dc.creator | Cavaliero, Arielle | |
dc.creator | Timmer, Sander | |
dc.creator | Bonfiglioli, Elena | |
dc.creator | Smith, Cairns | |
dc.creator | Scollard, David | |
dc.creator | Navarini, Alexander A. | |
dc.creator | Aerts, Ann | |
dc.creator | Ferres, Juan Lavista | |
dc.creator | Moraes, Milton O. | |
dc.date | 2022-02-10T18:27:52Z | |
dc.date | 2022-02-10T18:27:52Z | |
dc.date | 2022 | |
dc.date.accessioned | 2023-09-27T00:12:12Z | |
dc.date.available | 2023-09-27T00:12:12Z | |
dc.identifier | 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. | |
dc.identifier | 0140-6736 | |
dc.identifier | https://www.arca.fiocruz.br/handle/icict/51143 | |
dc.identifier | 10.1016/j.lana.2022.100192 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8898481 | |
dc.description | 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. | |
dc.format | application/pdf | |
dc.language | eng | |
dc.publisher | The Lancet | |
dc.rights | open access | |
dc.subject | Hanseníase | |
dc.subject | Inteligência artificial | |
dc.subject | AI | |
dc.subject | Diagnóstico baseado em imagem | |
dc.subject | Dermatologia | |
dc.subject | Lesões de pele | |
dc.subject | Al4lepra | |
dc.subject | Leprosy | |
dc.subject | Artificial intelligence | |
dc.subject | AI | |
dc.subject | Image-based diagnosis | |
dc.subject | Dermatology | |
dc.subject | Skin lesions | |
dc.subject | Al4leprosy | |
dc.title | Reimagining leprosy elimination with AI analysis of a combination of skin lesion images with demographic and clinical data | |
dc.type | Article | |