Report Summarizes Cancer Study Findings from Kerman University of Medical Sciences (Extracting cancer concepts from clinical notes using natural language processing: a systematic review).

A report from Kerman University of Medical Sciences discusses the use of natural language processing (NLP) to extract cancer concepts from clinical notes automatically. The study systematically reviewed papers that used NLP methods to identify cancer concepts from clinical notes. The researchers found that rule-based algorithms were the most commonly used for concept extraction, and the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) and Unified Medical Language System (UMLS) were the most commonly used terminologies. The study concluded that the use of NLP for extracting cancer concepts has increased in recent years, and suggested that future studies use rule-based algorithms for extracting concepts of other diseases as well. [Extracted from the article]