Artificial intelligence in the assistance of early diagnosis of Leprosy in the community by the Leprosy Suspection Questionnaire (LSQ)

• Grant number: 20/03157-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2020
• End date: October 31, 2020
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal Investigator: Marco Andrey Cipriani Frade
• Grantee: Mateus Mendonça Ramos Simões
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Symptoms of Leprosy-like illnesses have been reported since ancient times in China. Leprosy is defined as an infectious and contagious disease of a chronic nature, with dermatoneurological manifestations and high disabling conditions. Brazil has a high load for the disease, with 12.2 cases detected for every 100 thousand inhabitants, placing it in second in the world, behind India only. Although Brazil is aligned with the WHO strategy to reduce the load of the disease in the country, the diagnosis of Leprosy is still tardy, with many cases of patients already presenting disability. In endemic countries like Brazil, the situation maybe even worse, with estimates for the actual number of people affected by Leprosy being 6 to 8 times the number of cases of new detections. Seizing the democratization of the internet and smartphones, to which 99.7% and 92% of Brazilians have access respectively, it becomes interesting to create an application that uses artificial intelligence (AI) to inform users about the disease and that offer a test that provides the likelihood that they have Leprosy. With the advances of studies in the field of AI and Machine Learning, much medical diagnostic software use Bayes' Theorem to give an opinion. With the researches of Professor Marco Frade and Fred Bernardes (2015/2019) in Jardinópolis (SP), the consequent consolidation of the Leprosy Suspection Questionnaire (LSQ) and the clinical evaluations of the participants (3241 LSQs, of which 684 were clinically evaluated), if possible, the use of data from the LSQs filled in during the surveys and evaluations for the development of a AI algorithm with the possibility of its implementation as an application (APP) for smartphones that can spread information to the community about signs and symptoms of Leprosy (health education) and early diagnosis.