International Classification of Diseases for Oncology

International Classification of Diseases for Oncology PDF

Author: World Health Organization

Publisher:

Published: 2013-12-15

Total Pages: 252

ISBN-13: 9789240692121

DOWNLOAD EBOOK →

"The International Classification of Diseases for Oncology" (ICD-O) has been used for nearly 25 years as the standard tool for coding diagnoses of neoplasms in tumor and cancer registrars and in pathology laboratories. ICD-O is a dual classification with coding systems for both topography and morphology. The topography code describes the site of origin of the neoplasm and uses the same 3-character and 4-character categories as in the neoplasm section of Chapter II, ICD-10. The morphology code describes the characteristics of the tumor itself, including its cell type and biologic activity.In preparing this revised edition, the editors have made a special effort to change as few terms as possible, to add new terms at empty spaces, and to avoid reuse of previously assigned codes. While all topography codes remain the same as in the previous edition, morphology codes have been thoroughly reviewed and, where necessary, revised to increase their diagnostic precision and prognostic value.

Application of the International Classification of Diseases to Neurology

Application of the International Classification of Diseases to Neurology PDF

Author: World Health Organization

Publisher: World Health Organization

Published: 1997-10-02

Total Pages: 586

ISBN-13: 924154502X

DOWNLOAD EBOOK →

Gives specialists in the clinical neurosciences a detailed and authoritative instrument for coding virtually all recognized neurological conditions. Both neurological diseases and neurological manifestations of general diseases and injuries are included in this comprehensive coding tool. The volume is part of a growing family of specialty-based adaptations of ICD-10 which retain the core codes of the parent classification while providing extended detail at the fifth character and beyond. Now in its second edition ICD-NA has been revised to reflect current clinical concepts in the neurosciences as well as the new coding system introduced with ICD-10. The classification was finalized following extensive consultation with numerous professional organizations and international experts thus ensuring the representation of as many viewpoints as are practical and consistent. While remaining directly compatible with ICD-10 ICD-NA offers clinicians and researchers much greater precision allowing them to match an explicit diagnosis with a detailed code at the five- six or seven-character level. In addition a comprehensive alphabetical index and the extensive use of inclusion and exclusion terms provide considerable assistance in finding the correct category for any condition diagnosed. Apart from these opportunities for recording greater diagnostic detail the direct compatibility with ICD-10 facilitates comparisons between statistics compiled according to ICD-NA and national morbidity and mortality statistics compiled according to ICD-10. These features enhance the flexibility of ICD-NA making it suitable for use in morbidity statistics hospital record indexing and epidemiological research by government and other health agencies collecting statistical data under relatively few main headings or by individual physicians and researchers requiring a convenient tool for indexing their clinical and teaching material in sufficient detail. The revised classification should also facilitate the collection of epidemiological data comparisons of the prevalence of individual neurological diseases and identification of the risk factors for these diseases at both national and international levels. In addition to the detailed tabular list of neurological and related disorders the volume includes an explanation of the basic principles of classification and instructions for coding morphology codes for neoplasms relevant to neurology and neurosurgery and a 90-page index of diagnostic terms given in standard or official nomenclatures together with synonyms and eponyms.

Clinical Text Mining

Clinical Text Mining PDF

Author: Hercules Dalianis

Publisher: Springer

Published: 2018-05-14

Total Pages: 192

ISBN-13: 3319785036

DOWNLOAD EBOOK →

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.