Extracting cancer concepts from clinical notes using natural language processing: a systematic review.

Journal: BMC bioinformatics
Published Date: Oct 29, 2023

Abstract

BACKGROUND: Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This study aimed to systematically review studies that used NLP methods to identify cancer concepts from clinical notes automatically.

Authors

  • Maryam Gholipour
    Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran.
  • Reza Khajouei
    Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran.
  • Parastoo Amiri
    Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran.
  • Sadrieh Hajesmaeel Gohari
    Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Leila Ahmadian
    Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran. l.ahmadian@kmu.ac.ir.

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