AI in Healthcare: Examining Past, Present & Future Applications

This literature review provides an overview of artificial intelligence (AI) applications in healthcare, examining its past, present, and future. It highlights the increasing availability of healthcare data and the rapid progress of analytics techniques that power AI's paradigm shift in the medical field. The review covers various types of healthcare data, including structured and unstructured data, and discusses popular AI techniques such as machine learning methods (support vector machines, neural networks, deep learning) and natural language processing (NLP). Major disease areas utilizing AI tools, such as cancer, neurology, and cardiology, are explored, with a specific focus on AI applications in stroke, including early detection and diagnosis, treatment, outcome prediction, and prognosis evaluation. The review concludes with a discussion of pioneer AI systems like IBM Watson and the hurdles for real-world deployment of AI in healthcare. The study emphasizes the importance of clinically driven AI applications to assist and improve clinical practice.