AI-Driven Smart Healthcare Ecosystems: Advancing Disease Prediction Diagnosis, Digital Medicine, and Healthcare Governance

Abstract

Abstract: The Artificial Intelligence (AI) became one of the key elements of smart healthcare ecosystems for innovative approaches to disease prediction, disease diagnostics, digital medicine, and healthcare management. The topic of this research is the ways of application of AI to improve the delivery process in the hospital in the course of the systematic literature review. Secondary data collection sources for this research will be the reports of Authority Healthcare, conferences, and the peer-reviewed articles published in 2020-26. The usage of machine learning, deep learning, and intelligent decision support systems, particularly with regard to the early disease prediction, medical imaging, personalized therapy, telemedicine, remote patient monitoring, and digital therapeutics, are considered in the context of literature review. The three most popular AI algorithms, such as Random Forest and CNN and LSTM, were reviewed in order to investigate the role of these algorithms in predictive analytics, disease diagnostics, and health monitoring. The results show that the influence of AI on the improvement of diagnostic excellence, immediate clinical interventions, patient interaction, and healthcare management efficiency is enormous. Nonetheless, the following aspects, namely privacy of data, cybersecurity, bias, explainability, interoperability, and regulation, are among the challenges related to the research, which affect the responsible usage of the technology. Therefore, it can be said that the decentralized adoption of AI technologies in the proper regulation of smart healthcare systems could help optimize the quality and efficiency of treatment and digitalization would be sustainable. In order to ensure the fair, safe, and transparent usage of AI technologies, the future would show how to govern the processes effectively and responsibly.