Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23718, first published .
Leprosy Screening Based on Artificial Intelligence: Development of a Cross-Platform App

Leprosy Screening Based on Artificial Intelligence: Development of a Cross-Platform App

Leprosy Screening Based on Artificial Intelligence: Development of a Cross-Platform App

Journals

  1. Steyve N, Steve P, Ghislain M, Ndjakomo S, pierre E. Optimized real-time diagnosis of neglected tropical diseases by automatic recognition of skin lesions. Informatics in Medicine Unlocked 2022;33:101078 View
  2. Li X, Yang J, Zhang L, Jin G, Xu L, Fang F, Li Y, Wei P. A Bibliometric Analysis of Leprosy during 2000–2021 from Web of Science Database. International Journal of Environmental Research and Public Health 2022;19(14):8234 View
  3. Matos D, Torres M, da Silva L, dos Santos C, de Oliveira F, de Araújo M, de Oliveira Serra M. Hansenapp: Development of a mobile application to assist primary healthcare providers to control leprosy. Tropical Medicine & International Health 2022;27(8):719 View
  4. Hedrich N, Lovey T, Kuenzli E, Epéron G, Blanke U, Schlagenhauf P. Infection tracking in travellers using a mobile app (ITIT): The pilot study. Travel Medicine and Infectious Disease 2023;52:102526 View
  5. Harsono A, Susiarno H, Suardi D, Owen L, Fauzi H, Kireina J, Wahid R, Carolina J, Mantilidewi K, Hidayat Y. Cervical pre-cancerous lesion detection: development of smartphone-based VIA application using artificial intelligence. BMC Research Notes 2022;15(1) View
  6. Sharma M, Singh P. Advances in the Diagnosis of Leprosy. Frontiers in Tropical Diseases 2022;3 View
  7. Yi-No Kang E, Chen D, Chen Y. Associations between literacy and attitudes toward artificial intelligence–assisted medical consultations: The mediating role of perceived distrust and efficiency of artificial intelligence. Computers in Human Behavior 2023;139:107529 View
  8. Wichmann R, Fagundes T, de Oliveira T, Batista A, Chiavegatto Filho A, Roman-Gonzalez A. Physician preference for receiving machine learning predictive results: A cross-sectional multicentric study. PLOS ONE 2022;17(12):e0278397 View
  9. Cunha E, Marçal P, Gama R, de Oliveira L, Pinheiro R, Sarno E, Brito-de-Sousa J, de Souza M, Fairley J, Valente T, Velloso-Rodrigues C, Martins-Filho O, de Oliveira D, Fraga L. Interplay among differential exposure to Mycobacterium leprae and TLR4 polymorphism impacts the immune response in household contacts of leprosy patients. Frontiers in Immunology 2023;14 View
  10. Costa W, de Oliveira A, Aguilar G, dos Santos L, dos Santos L, Donato D, Foresto F, Frade M. A Review of Software and Mobile Apps to Support the Clinical Diagnosis of Hansen Disease. JMIR Dermatology 2023;6:e47142 View
  11. Anzaku E, Mohammed M, Ozbulak U, Won J, Hong H, Krishnamoorthy J, Van Hoecke S, Magez S, Van Messem A, De Neve W. Tryp: a dataset of microscopy images of unstained thick blood smears for trypanosome detection. Scientific Data 2023;10(1) View
  12. Fernandes J, Teles A, Fernandes T, Lima L, Balhara S, Gupta N, Teixeira S. Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review. Journal of Clinical Medicine 2023;13(1):180 View
  13. Vernal S, Gomes C. Editorial: New insights in leprosy (Hansen's disease). Frontiers in Medicine 2024;11 View

Books/Policy Documents

  1. Nyatte S, Perabi S, Abessolo G, Ndjakomo Essiane S, Ele P. Proceeding of the 3rd International Conference on Electronics, Biomedical Engineering, and Health Informatics. View