Research on real-world knowledge mining and knowledge graph completion(Ⅲ):structured information extraction from real world data of bladder cancer based on regular expression
MA Wenhao
SHI Hanyu
HUANG Qiao
HUANG Xing
WANG Yongbo
WANG Shichun
REN Xiangying
SHI Yue
JIN Yinghui
YAN Siyu
Abstract：With the development of medical big data,the real-world study(RWS)has received increasing attention in recent years,and has a good promising prospect.However,there are still some challenges in the implementation of RWS that has led to extensive discussion among scholars.The most urgent issue currently to be addressed is the unstructured nature of real-world data(RWD).Based on regular expressions,this study used rule-based information extraction method to extract structured information from admission records,pathological reports,surgical records,and image records of bladder cancer patients in Zhongnan Hospital of Wuhan University in recent years,and evaluated the extraction effects with accuracy and recall as indicators,aiming to provide reference for subsequent research.
Keywords：Real-world dataInformation extractionRegular expressionNatural language processingElectronic medical record dataBladder cancer
Publication Date：2024-06-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 312-321 )