Big Data and Digital Health, a Biomedical Engineering-Based Approach: a narrative review from the Scopus database (2010-2024). (#2005)

Authors

Alburuqueque Arana, Fausta Elizabeth

Pérez Najera, Celín

Almandoz Vilcabana, Ana María Mercedes

Paredes Morales, Ana Elizabeth

Rázuri Rubio, Heidi Halina

Abstract

This narrative review analyzes the evolution and integration of Big Data and digital health in Latin America from the perspective of biomedical engineering during the period 2010-2024. The research focuses on examining trends, challenges and opportunities in the implementation of digital technologies in the Latin American health sector, with special emphasis on artificial intelligence and big data analytics applications. Through a systematic search in the Scopus database, relevant publications addressing four main areas were identified and analyzed: AI-assisted diagnosis (40% of the studies), optimization of hospital systems (25%), disease prediction and prevention (20%), and personalized medicine (15%). The results reveal a significant transformation in healthcare delivery, driven by the COVID-19 pandemic, which has acted as a catalyst for the accelerated adoption of digital solutions. Key findings indicate that while the region has experienced remarkable progress in the implementation of digital health technologies, significant challenges remain related to technological infrastructure, training of specialized personnel and data protection. The research highlights the importance of developing solutions adapted to the Latin American context, considering socioeconomic, cultural and geographic factors specific to the region.