Natural Language Processing and Text Mining

This chapter provides a comprehensive overview of natural language processing (NLP) and its applications, with a particular focus on its integration with medical and healthcare fields. Key topics include fundamental NLP tasks such as lexical analysis, syntactic and semantic analysis, information extraction, text classification, and high-level applications like machine translation and question-answering systems. In the medical domain, NLP plays a pivotal role, facilitating tasks like biomedical named entity recognition, relationship extraction, and medical knowledge mining. It transforms unstructured texts, such as clinical notes and research articles, into structured data for applications like drug discovery, adverse drug event detection, electronic medical record (EMR) management, and medical decision support. The chapter also introduces essential NLP techniques, including sequence labeling, classification, and generation, and highlights their role in deep learning-based methodologies like bidirectional long short-term memory (Bi-LSTM) networks. Additionally, the chapter explores advanced applications like event extraction, underscoring NLP’s transformative potential in the medical and biomedical research domains.