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Advanced analytics for the automation of medical systematic reviews

Author

Listed:
  • Prem Timsina

    (Dakota State University)

  • Jun Liu

    (Dakota State University)

  • Omar El-Gayar

    (Dakota State University)

Abstract

While systematic reviews (SRs) are positioned as an essential element of modern evidence-based medical practice, the creation and update of these reviews is resource intensive. In this research, we propose to leverage advanced analytics techniques for automatically classifying articles for inclusion and exclusion for systematic reviews. Specifically, we used soft-margin polynomial Support Vector Machine (SVM) as a classifier, exploited Unified Medical Language Systems (UMLS) for medical terms extraction, and examined various techniques to resolve the class imbalance issue. Through an empirical study, we demonstrated that soft-margin polynomial SVM achieves better classification performance than the existing algorithms used in current research, and the performance of the classifier can be further improved by using UMLS to identify medical terms in articles and applying re-sampling methods to resolve the class imbalance issue.

Suggested Citation

  • Prem Timsina & Jun Liu & Omar El-Gayar, 2016. "Advanced analytics for the automation of medical systematic reviews," Information Systems Frontiers, Springer, vol. 18(2), pages 237-252, April.
    • Handle: RePEc:spr:infosf:v:18:y:2016:i:2:d:10.1007_s10796-015-9589-7
    DOI: 10.1007/s10796-015-9589-7
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    Citations

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    Cited by:

    1. Yoon Sang Lee & Chulhwan Chris Bang, 2022. "Framework for the Classification of Imbalanced Structured Data Using Under-sampling and Convolutional Neural Network," Information Systems Frontiers, Springer, vol. 24(6), pages 1795-1809, December.
    2. Aaron W. Baur, 2017. "Harnessing the social web to enhance insights into people’s opinions in business, government and public administration," Information Systems Frontiers, Springer, vol. 19(2), pages 231-251, April.
    3. Saba Bashir & Usman Qamar & Farhan Hassan Khan, 2018. "WebMAC: A web based clinical expert system," Information Systems Frontiers, Springer, vol. 20(5), pages 1135-1151, October.
    4. Atreyi Kankanhalli & Jungpil Hahn & Sharon Tan & Gordon Gao, 2016. "Big data and analytics in healthcare: Introduction to the special section," Information Systems Frontiers, Springer, vol. 18(2), pages 233-235, April.
    5. Saba Bashir & Usman Qamar & Farhan Hassan Khan, 0. "WebMAC: A web based clinical expert system," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    6. Aaron W. Baur, 0. "Harnessing the social web to enhance insights into people’s opinions in business, government and public administration," Information Systems Frontiers, Springer, vol. 0, pages 1-21.

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