Catálogo de publicaciones - libros

This chapter gives a short introduction of the research area of clinical text mining.

This chapter describes the history of patient records and the languages used therein.

This chapter is about the use of patient records and the requirements the different health professionals, such as physicians and nurses, have on the patient record system.

This chapter specifically details the linguistic characteristics of patient record text in the form of spelling errors, domain specific abbreviations, negation and assertion expressions, etc. for English, Swedish and other languages.

This chapter presents the different medical classifications and terminologies as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, ATC etc.

This chapter describes the metrics for the evaluation of information retrieval and natural language processing systems, the annotation techniques and evaluation metrics and the concepts of training, development and evaluations sets for information retrieval systems.

This chapter presents the basic building blocks for clinical text processing and relates them to the building blocks for standard text processing using natural languages processing techniques.

This chapter presents the computational methods for text analysis and text classification, including both rule-based and machine learning-based methods such as unsupervised and supervised methods.

This chapter discusses ethical issues while working with sensitive material such as patient records, how to apply for ethical permission, the safe storage of sensitive data and other privacy-related topics.

This chapter presents various applications of clinical text mining that all use the electronic patient record text as input data.