This paper provides a detailed summary and tutorial on natural language processing (NLP) and current NLP system architecture. The medical informatics generalist who is unfamiliar with NLP concepts and/or has a limited understanding of the present state of the art. In this vast topic, we discuss the historical history of NLP and highlight frequent NLP sub-problems. After that, we give a rundown of some of the most notable achievements in medical NLP. We describe how current NLP architectures are developed, with an overview of the Apache Foundation's Unstructured Information, after offering a brief discussion of typical machine-learning techniques that are already being utilised for various NLP sub problems. Finally, we examine probable future paths for NLP, as well as IBM Watson's potential effect on the medical profession.