ARTIFICIAL INTELLIGENCE IN ADDRESSING NEGLECTED TROPICAL DISEASES IN THE BRAZILIAN AMAZON: ADVANCES, CHALLENGES, AND FUTURE PERSPECTIVES FOR MULTIPROFESSIONAL HEALTHCARE PRACTICE

Résumé fourni par la source

Neglected tropical diseases remain a major global public health challenge, disproportionately affecting socially vulnerable populations and regions with limited access to healthcare services, such as the Brazilian Amazon. In this context, Artificial Intelligence has emerged as an innovative technology capable of strengthening diagnostic strategies, epidemiological surveillance, environmental monitoring, and clinical decision support, contributing to more effective control of these diseases. This study aimed to analyze the scientific evidence regarding the application of Artificial Intelligence in addressing neglected tropical diseases in the Brazilian Amazon, discussing its advances, limitations, and future perspectives for multiprofessional healthcare practice. A qualitative, descriptive, and analytical integrative literature review was conducted using publications indexed in PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, the Virtual Health Library, and Google Scholar, in addition to official documents from national and international health organizations. The findings demonstrated that machine learning algorithms, computer vision systems, and predictive models have significant potential to support early diagnosis, identify high-risk epidemiological areas, optimize health surveillance, and improve healthcare planning in remote regions. However, challenges related to technological infrastructure, data quality, ethical issues, health information security, and professional training still limit the large-scale implementation of these technologies. It is concluded that Artificial Intelligence represents an important ally in combating neglected tropical diseases when implemented ethically, safely, and in integration with public health policies, scientific research, and collaborative multiprofessional practice, contributing to more effective, equitable, and resilient healthcare systems in the Brazilian Amazon.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.