Advancing Healthcare through Artificial Intelligence: A Comprehensive Review of Machine Learning Applications in Health Informatics

Abstract

Deep learning and other types of Artificial Intelligence (AI) are quickly changing the healthcare and health informatics landscape to allow deeper data analysis, predictive modeling, and customized care of patients. Convolutional and recurrent neural networks are examples of deep learning architecture that have demonstrated spectacular performance in medical imaging, disease prediction, drug discovery and telemedicine applications. Health informatics will ensure the required data collection, data storage, and integration structures that will ensure efficient and safe operation of AI models. The emerging techniques are mitigating these drawbacks despite the various problems posed by data quality, interpretability, ethical issues, and infrastructure needs. The review presents the existing innovations, uses, challenges, and prospects, focusing on the synergistic opportunities of AI and deep learning to transform the modern healthcare.