Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (11A): 524-530.doi: 10.11896/jsjkx.200400062

• Big Data & Data Science • Previous Articles     Next Articles

Mining Nuclear Medicine Diagnosis Text for Correlation Extraction Between Lesions and Their Representations

HAN Cheng-cheng1,2, LIN Qiang1,2, MAN Zheng-xing1,2, CAO Yong-chun1,2, WANG Hai-jun3, WANG Wei-lan4   

  1. 1 School of Mathematics and Computer Science,Northwest Minzu University,Lanzhou 730030,China
    2 Key Laboratory of Streaming Data Computing Technologies and Application,Northwest Minzu University,Lanzhou 730012,China
    3 Department of Nuclear Medicine,Gansu Provincial Hospital,Lanzhou 730020,China
    4 Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education,Northwest Minzu University,Lanzhou 730030,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:HAN Cheng-cheng,born in 1994,postgraduate,is a member of China Computer Federation.Her main research interests include data mining and intelligent information processing.
    LIN Qiang,born in 1979,Ph.D,asso-ciate professor,master's supervisor,is a member of China Computer Federation.His main research interests include medical image computing,data stream mining,pervasive computing and intelligent information processing.
  • Supported by:
    This work was supported by the Northwest Minzu University for Central University Basic Scientific Research Operating Expenses Special Fund to Support the Graduate Program (Yxm2020101),National Natural Science Foundation of China (61562075),Gansu Provincial First-class Discipline Program of Northwest Minzu University (11080305) and Program for Innovative Research Team of SEAC ([2018] 98).

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Abstract: Medical imaging is an indispensable part of the diagnosis and treatment of diseases in modern clinical medicine.SPECT is the main functional imaging technology and has been widely used in the diagnosis and treatment of diseases such as tumor bone metastasis.The SPECT diagnostic text contains several aspects of patients' personal information,image description,and suggested results.In order to accurately extract the association between disease and its representation in the diagnostic text of SPECT nuclear medicine bone imaging,a method of mining association rules of nuclear medicine text based on data mining is proposed.Firstly,a method of SPECT medical diagnostic text preprocessing and uniform coding is proposed to solve the problems of information redundancy,data loss and inconsistent expression.Secondly,the classical association rule mining algorithm Apriori is applied to propose the association mining algorithm between lesions and their representations.Finally,the proposed method is validated with a set of real-world SPECT nuclear medical diagnostic text data from the department of nuclear medicine in a 3a grade hospitals,and the results show that the proposed method is able to objectively extracted the association between the disease and its representation,and the average objectivity is more than 90%.

Key words: Diagnostic text, Extraction of association rules, Medical imaging, SPECT nuclear medicine, Text mining

CLC Number: 

  • TP391
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