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AI-Driven Smart Auditory Health Systems: Bridging Audiology and Public Health in Low- and Middle-Income Countries
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Review Article
AI-Driven Smart Auditory Health Systems: Bridging Audiology and Public Health in Low- and Middle-Income Countries
Hearing loss is a critical global health issue that affects over 1.5 billion people worldwide, with a disproportionate burden in Low- and Middle-Income Countries (LMICs). These regions face significant challenges, including limited access to audiological services, a shortage of healthcare professionals, and a lack of affordable hearing solutions. These barriers lead to delayed diagnoses, inadequate management, and a significant negative impact on individuals' quality of life, education, and employment opportunities. The advent of Artificial Intelligence (AI) and advanced technologies offers innovative pathways to address these longstanding challenges. This review introduces the AI-driven smart Auditory Health Systems (SAHS) concept. This holistic approach integrates AI, wearable devices, Internet of Things (IoT) technology, and big data analytics to enhance the prevention, diagnosis, and management of auditory disorders. SAHS systems can provide real-time monitoring, early detection of hearing loss, and personalized care solutions tailored to individual and population needs. These systems offer community-level interventions, including noise pollution monitoring and data-driven public health strategies. Focusing on the LMIC context, this review explores the technological framework, applications, ethical considerations, and logistical challenges of implementing SAHS. By leveraging these advanced technologies, SAHS has the potential to bridge gaps in healthcare access, improve health outcomes, and transform auditory healthcare delivery in resource-constrained settings. This review underscores the importance of collaborative efforts in research, policy development, and capacity building to ensure equitable adoption of SAHS, thereby addressing hearing health disparities globally.
