Analysis of big data in colonoscopy to determine whether inverval lesions are de novo, missed or incompletely removed

Piet C. de Groen, Wallapak Tavanapong, Junghwan Oh, Johnny Wong

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

Abstract

We have created a system that automatically records the inside-the-patient images of each colonoscopy in de-identified fashion. At present this “big data” database contains around 100 TB of de-identified endoscopy data. Interval colorectal cancers (CRCs) are CRCs that develop despite periodic colonoscopy and are due to de novo tumor growth, a missed lesion or incomplete lesion removal. Using a combination of location, date, time and image information we were able to find a video file within our de-identified big data from a prior colonoscopy that belonged to a patient with a recently diagnosed large interval lesion. Analysis of the video file showed that a large lesion was incompletely removed. Analysis of big endoscopy datasets has the potential to resolve the cause of most if not all interval lesions and CRCs and can provide specific, focused education to endoscopists related to their individual limitations.

Original languageEnglish (US)
Title of host publicationSmart Education and e-Learning 2017
EditorsVladimir L. Uskov, Robert J. Howlett, Lakhmi C. Jain, Lakhmi C. Jain, Robert J. Howlett, Lakhmi C. Jain
PublisherSpringer Science and Business Media Deutschland GmbH
Pages310-320
Number of pages11
ISBN (Print)9783319594507
DOIs
StatePublished - Jan 1 2017
Event4th International KES conference on Smart Education and Smart e-Learning, SEEL 2017 - Vilamoura, Algarve, Portugal
Duration: Jun 21 2017Jun 23 2017

Publication series

NameSmart Innovation, Systems and Technologies
Volume75
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Other

Other4th International KES conference on Smart Education and Smart e-Learning, SEEL 2017
CountryPortugal
CityVilamoura, Algarve
Period6/21/176/23/17

Keywords

  • Colonoscopy
  • Education
  • Interval colorectal cancer
  • Quality features
  • Video stream analysis

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    de Groen, P. C., Tavanapong, W., Oh, J., & Wong, J. (2017). Analysis of big data in colonoscopy to determine whether inverval lesions are de novo, missed or incompletely removed. In V. L. Uskov, R. J. Howlett, L. C. Jain, L. C. Jain, R. J. Howlett, & L. C. Jain (Eds.), Smart Education and e-Learning 2017 (pp. 310-320). (Smart Innovation, Systems and Technologies; Vol. 75). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-59451-4_31