INTEGRATING ARTIFICIAL INTELLIGENCE AND BIG DATA IN MOBILE HEALTH: A SYSTEMATIC REVIEW OF INNOVATIONS AND CHALLENGES IN HEALTHCARE SYSTEMS

Abstract

This systematic review explores the integration of Artificial Intelligence (AI) and Big Data in mobile health (mHealth) and their transformative impact on healthcare systems. Analysing 25 peer-reviewed articles, the review delves into the utilisation, innovations, and inherent challenges of AI and Big Data in various healthcare settings. The findings reveal that AI and Big Data significantly enhance diagnostic precision, personalise treatment strategies, and streamline healthcare operations. However, this technological advancement is not without its complexities. Key challenges identified include ethical dilemmas, data privacy and security issues, and preserving the human element within healthcare. The review underscores the risk of an over-reliance on AI and the criticality of using unbiased, representative data sets. The integration of AI into clinical practices, while promising, demands rigorous oversight and ethical governance. The review concludes that the successful adoption of AI and Big Data in healthcare hinges on a balanced approach that harmonises technological innovation with ethical, equitable, and human-centred healthcare practices. If managed effectively, this integration offers the potential for significant improvements in patient outcomes and operational efficiency yet requires vigilant management of the challenges to realise its benefits fully.