Development of deep learning algorithm for detection of colorectal cancer in EHR data

Yu Hsiang Wang, Phung Anh Nguyen, Md Mohaimenul Islam, Yu Chuan Li, Hsuan Chia Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal cancer in Taiwanese adults. We collected data of 58152 patients from the Taiwan National Health Insurance database from 1999 to 2013. All patients' comorbidities and medications history were included in the development of the convolution neural network (CNN) model. We also used 3-year medical data of all patients before the diagnosed colorectal cancer (CRC) as the dimensional time in the model. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were computed to measure the performance of the model. The results showed the mean (SD) of AUC of the model was 0.922 (0.004). Moreover, the performance of the model observed the sensitivity of 0.837, specificity of 0.867, and 0.532 for PPV value. Our study utilized CNN to develop a prediction model for CRC, based on non-image and multi-dimensional medical records.

Original languageEnglish
Title of host publicationMEDINFO 2019
Subtitle of host publicationHealth and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
EditorsBrigitte Seroussi, Lucila Ohno-Machado, Lucila Ohno-Machado, Brigitte Seroussi
PublisherIOS Press
Pages438-441
Number of pages4
ISBN (Electronic)9781643680026
DOIs
Publication statusPublished - Aug 21 2019
Event17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, France
Duration: Aug 25 2019Aug 30 2019

Publication series

NameStudies in Health Technology and Informatics
Volume264
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference17th World Congress on Medical and Health Informatics, MEDINFO 2019
CountryFrance
CityLyon
Period8/25/198/30/19

Fingerprint

Learning algorithms
Colorectal Neoplasms
Learning
Area Under Curve
Sensitivity and Specificity
Neural Networks (Computer)
National Health Programs
Taiwan
ROC Curve
Medical Records
Comorbidity
Convolution
Databases
Health insurance
Neural networks
Deep learning

Keywords

  • Algorithms
  • Colorectal Neoplasms
  • Electronic Health Records

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Wang, Y. H., Nguyen, P. A., Mohaimenul Islam, M., Li, Y. C., & Yang, H. C. (2019). Development of deep learning algorithm for detection of colorectal cancer in EHR data. In B. Seroussi, L. Ohno-Machado, L. Ohno-Machado, & B. Seroussi (Eds.), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics (pp. 438-441). (Studies in Health Technology and Informatics; Vol. 264). IOS Press. https://doi.org/10.3233/SHTI190259

Development of deep learning algorithm for detection of colorectal cancer in EHR data. / Wang, Yu Hsiang; Nguyen, Phung Anh; Mohaimenul Islam, Md; Li, Yu Chuan; Yang, Hsuan Chia.

MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. ed. / Brigitte Seroussi; Lucila Ohno-Machado; Lucila Ohno-Machado; Brigitte Seroussi. IOS Press, 2019. p. 438-441 (Studies in Health Technology and Informatics; Vol. 264).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, YH, Nguyen, PA, Mohaimenul Islam, M, Li, YC & Yang, HC 2019, Development of deep learning algorithm for detection of colorectal cancer in EHR data. in B Seroussi, L Ohno-Machado, L Ohno-Machado & B Seroussi (eds), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 264, IOS Press, pp. 438-441, 17th World Congress on Medical and Health Informatics, MEDINFO 2019, Lyon, France, 8/25/19. https://doi.org/10.3233/SHTI190259
Wang YH, Nguyen PA, Mohaimenul Islam M, Li YC, Yang HC. Development of deep learning algorithm for detection of colorectal cancer in EHR data. In Seroussi B, Ohno-Machado L, Ohno-Machado L, Seroussi B, editors, MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. IOS Press. 2019. p. 438-441. (Studies in Health Technology and Informatics). https://doi.org/10.3233/SHTI190259
Wang, Yu Hsiang ; Nguyen, Phung Anh ; Mohaimenul Islam, Md ; Li, Yu Chuan ; Yang, Hsuan Chia. / Development of deep learning algorithm for detection of colorectal cancer in EHR data. MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. editor / Brigitte Seroussi ; Lucila Ohno-Machado ; Lucila Ohno-Machado ; Brigitte Seroussi. IOS Press, 2019. pp. 438-441 (Studies in Health Technology and Informatics).
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