Natural language processing: an introduction

Abstract

Objectives To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design.

Target audience This tutorial targets the medical informatics generalist who has limited acquaintance with the principles behind NLP and/or limited knowledge of the current state of the art.

Scope We describe the historical evolution of NLP, and summarize common NLP sub-problems in this extensive field. We then provide a synopsis of selected highlights of medical NLP efforts. After providing a brief description of common machine-learning approaches that are being used for diverse NLP sub-problems, we discuss how modern NLP architectures are designed, with a summary of the Apache Foundation's Unstructured Information Management Architecture. We finally consider possible future directions for NLP, and reflect on the possible impact of IBM Watson on the medical field.

Natural language processing, Introduction, clinical NLP, knowledge bases, machine learning, predictive modeling, statistical learning, privacy technology