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Automatic Classification of Cancer Pathology Reports: A Systematic Review
2022
Journal of Pathology Informatics
Pathology reports primarily consist of unstructured free text and thus the clinical information contained in the reports is not trivial to access or query. Multiple natural language processing (NLP) techniques have been proposed to automate the coding of pathology reports via text classification. In this systematic review, we follow the guidelines proposed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA; Page et al., 2020: BMJ.) to identify the NLP systems for
doi:10.1016/j.jpi.2022.100003
pmid:35242443
pmcid:PMC8860734
fatcat:c5hve3ottnb6hbcalimya6u3ae