Text Mining in Radiology Reports

• Main Authors: GONG, Tianxia, TAN, Chew Lim, Tze-Yun LEONG, LEE, Cheng Kiang, PANG, Boon Chuan, LIM, C. C. Tchoyoson, TIAN, Qi, TANG, Suisheng, ZHANG, Zhuo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2008
• Subjects: Computer Sciences; Medicine and Health Sciences; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/3067; https://ink.library.smu.edu.sg/context/sis_research/article/4067/viewcontent/P_ID_52339_Gong_TextMiningRadiologyReports.pdf
• Institution: Singapore Management University

Medical text mining has gained increasing interest in recent years. Radiology reports contain rich information describing radiologist's observations on the patient's medical conditions in the associated medical images. However as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and used, unless proper text mining has been applied. In this paper we propose a text mining system to extract and use the information in radiology reports. The system consists of three main modules: a medical finding extractor a report and image retriever and a text-assisted image feature extractor In evaluation, the overall precision and recall for medical finding extraction are 9.5.5% and 87.9% respectively, and for all modifiers of the medical findings 88.2% and 82.8% respectively. The overall result of report and image retrieval module and text-assisted image feature extraction module is satisfactory to radiologists.