Deep Learning and Multimodal Artificial Neural Network Architectures for Disease Diagnosis and Clinical Applications

Machine learning is an important utility of artificial intelligence that provides systems with the capacity to automatically examine and enhance action without being specially programmed. Deep learning is a subset of machine learning where innovations have led to the construction of several novel deep neural network architectures that can be used for the classification of large data sets. In India, the healthcare industry has become one of the essential service sectors. The generation of large amounts of healthcare data and the lack of insight from that data are significant problems in the healthcare sector. An extensive amount of multimodal information like clinical symptoms, signals, sounds, and outputs of imaging devices are currently available to clinical specialists. Artificial intelligence, machine learning, and deep learning techniques can be employed for efficient knowledge discovery from healthcare data. This chapter reviews the power, applicability, and achievements of the aforementioned techniques in the medical field and also summarizes the popular deep neural network architectures. This chapter contributes a mathematical model to the existing literature. Exploring this framework through experimental studies in the future will provide new insights into disease prediction and labeling of medical images.