A Comprehensive Artificial Intelligence-Driven Healthcare System

Abstract

The World Health Organization (WHO) states that millions of people worldwide suffer from severe health conditions like diabetes, cardiovascular diseases, stroke, autism, and epilepsy. Some of these conditions, like diabetes, have been on the rise in low-and middle-income countries (LMICs) recently. These conditions have a significant impact on mortality, disability, economic losses, and physical and emotional suffering. However, with more accurate diagnosis, early detection, and prediction of occurrence, these conditions can be treated and managed more effectively, and in some cases, even prevented. This paper presents a comprehensive healthcare system that utilizes artificial intelligence (AI), including large language models (LLMs)–such as Bard and GPT-4 (and their improved future variants), deep learning neural networks, and machine learning platforms such as TensorFlow, electronic health records (EHR), as well as conventional and innovative three-dimensional multilayer EEG systems. The system permits the incorporation of genetic, lifestyle, and environmental information that provides more accurate representations of the participant’s environment and leads to improved health outcomes. This will provide actionable insights for clinical decision support in the early detection, diagnosis, treatment, management, prediction, and prevention of various conditions, including diabetes, cardiovascular diseases, stroke, autism, and epilepsy-saving lives and improving living conditions by reducing the economic, social, psychological and physical burden of the conditions so predicted and possibly prevented, detected early, diagnosed, treated and managed more efficiently. Additionally, the system aims to facilitate practical human-machine interfaces (HMIs) such as brain computer interfaces (BCIs) and progress towards computer-mediated brain-to-brain communication. It also seeks to enhance our understanding of the human brain’s functioning in both normal and diseased states, which can be used for the rehabilitation of individuals with neurological conditions and to create innovative ways for healthy individuals to interact with their environment and improve their lives.