Automated data extraction tool (DET) for external applications in radiotherapy

被引:1
|
作者
Gurjar, Mruga [1 ]
Lindberg, Jesper [1 ,2 ,3 ]
Bjork-Eriksson, Thomas [4 ]
Olsson, Caroline [1 ,3 ]
机构
[1] Univ Gothenburg, Inst Clin Sci, Sahlgrenska Acad, Med Radiat Sci, Gothenburg, Sweden
[2] Sahlgrens Univ Hosp, Dept Med Phys & Biomed Engn, Gothenburg, Sweden
[3] Reg Canc Ctr West, Western Sweden Healthcare Reg, Gothenburg, Sweden
[4] Univ Gothenburg, Inst Clin Sci, Sahlgrenska Acad, Dept Oncol, Gothenburg, Sweden
基金
瑞典研究理事会;
关键词
Radiotherapy; Data extraction; Data cleaning; Automation;
D O I
10.1016/j.tipsro.2022.12.001
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose: Oncological Information Systems (OIS) manage information in radiotherapy (RT) departments. Due to database structure limitations, stored information can rarely be directly used except for vendor-specific purposes. Our aim is to enable the use of such data in various external applications by creating a tool for automatic data extraction, cleaning and formatting. Methods and materials: We used OIS data from a nine-linac RT department in Sweden (70 weeks, 2015-16). Extracted data included patients' referrals and appointments with details for RT sub-tasks. The data extraction tool to prepare the data for external use was built in C# programming language. It used excel-automation queries to remove unassigned/duplicated values, substitute missing data and perform application-specific calculations. Descriptive statistics were used to verify the output with the manually prepared dataset from the corresponding time period. Results: From the initial raw data, 2030 (51 %)/907 (23 %) patients had known curative and palliative treatment intent for 84 different cancer diagnoses. After removal of incomplete entries, 373 (10 %) patients had unknown treatment intents which were substituted based on the known curative/palliative ratio. Automatically- and manuallyprepared datasets differed < 1 % for Mould, Treatment planning, Quality assurance and +/- 5 % for Fractions and Magnetic resonance imaging with overestimations in 80/140 (57 %) entries by the tool. Conclusion: We successfully implemented a software tool to prepare ready-touse OIS datasets for external applications. Our evaluations showed overall results close to the manually-prepared dataset. The time taken to prepare the dataset using our automated strategy can reduce the time for manual preparation from weeks to seconds.
引用
收藏
页数:7
相关论文
共 50 条
  • [31] Introducing automated polymer data extractor tool
    Dai, Chunlei
    Schmidt, Kristin
    Zubarev, Dmitry
    Piunova, Victoria
    Surugucchi, Krishnakumar
    Sanders, Daniel
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 258
  • [32] STANDARDS, OPTIONS AND GUIDELINES FOR APPLICATIONS IN EXTERNAL RADIOTHERAPY AND CURIETHERAPY IN ONCOLOGY
    BEY, P
    GABORIAUD, G
    PEIFFERT, D
    ALETTI, P
    COSSET, JM
    BULLETIN DU CANCER, 1995, 82 (10) : 811 - 822
  • [33] Time Factor in External Radiotherapy: Radiobiological Mechanisms and Clinical Applications
    Maghous, Abdelhak
    Marnouche, El-Amin
    Hommadi, Mouhcine
    Belemlih, Maroua
    Zaghba, Noha
    Ennadif, Ayoub
    Bazine, Amine
    Lalya, Issam
    Andaloussi Saghir, Khalid
    Elmarjany, Mohamed
    Hadadi, Khalid
    Sifat, Hassan
    INDIAN JOURNAL OF GYNECOLOGIC ONCOLOGY, 2024, 22 (01)
  • [34] Time Factor in External Radiotherapy: Radiobiological Mechanisms and Clinical Applications
    Abdelhak Maghous
    El-Amin Marnouche
    Mouhcine Hommadi
    Maroua Belemlih
    Noha Zaghba
    Ayoub Ennadif
    Amine Bazine
    Issam Lalya
    Khalid Andaloussi Saghir
    Mohamed Elmarjany
    Khalid Hadadi
    Hassan Sifat
    Indian Journal of Gynecologic Oncology, 2024, 22
  • [35] ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information
    Abad, Zahra Shakeri Hossein
    Gervasi, Vincenzo
    Zowghi, Didar
    Barker, Ken
    2018 5TH INTERNATIONAL WORKSHOP ON ARTIFICIAL INTELLIGENCE FOR REQUIREMENTS ENGINEERING (AIRE 2018), 2018, : 8 - 14
  • [36] Smart Cognitive HMI With Automated Knowledge Extraction for Machine Tool
    Park, Jongsu
    Son, Jinho
    Cho, Seongwoo
    Um, Jumyung
    IEEE ACCESS, 2025, 13 : 120 - 134
  • [37] CrashScope: A Practical Tool for Automated Testing of Android Applications
    Moran, Kevin
    Linares-Vasquez, Mario
    Bernal-Cardenas, Carlos
    Vendome, Christopher
    Poshyvanyk, Denys
    PROCEEDINGS OF THE 2017 IEEE/ACM 39TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING COMPANION (ICSE-C 2017), 2017, : 15 - 18
  • [38] HADA: An automated tool for hardware dimensioning of AI applications
    De Filippo, Allegra
    Borghesi, Andrea
    Boscarino, Andrea
    Milano, Michela
    KNOWLEDGE-BASED SYSTEMS, 2022, 251
  • [39] Optimizing Practical Implementation of Automated Radiotherapy Treatment Planning Tool: A Survey
    McGinnis, Gwendolyn
    Ning, Matthew
    Makufa, Remigio
    Cardenas, Carlos
    Grover, Surbhi
    Court, Laurence E.
    Smith, Grace
    AMERICAN JOURNAL OF CLINICAL ONCOLOGY-CANCER CLINICAL TRIALS, 2021, 44 (10): : S125 - S126
  • [40] Applications of Automated Model's Extraction in Enterprise Systems
    Marinescu, Cristina
    ICSOFT: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGIES, 2019, : 254 - 261