Application of artificial intelligence in capsule endoscopy: Where are we now?

Youngbae Hwang, Junseok Park, Yun Jeong Lim, Hoon Jai Chun

    Research output: Contribution to journalReview articlepeer-review

    29 Citations (Scopus)


    Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist to review the operation and examine the lesions. To reduce the tedious review time and increase the accuracy of medical examinations, various approaches have been reported based on artificial intelligence for computer-aided diagnosis. Recently, deep learning–based approaches have been applied to many possible areas, showing greatly improved performance, especially for image-based recognition and classification. By reviewing recent deep learning–based approaches for clinical applications, we present the current status and future direction of artificial intelligence for capsule endoscopy.

    Original languageEnglish
    Pages (from-to)547-551
    Number of pages5
    JournalClinical Endoscopy
    Issue number6
    Publication statusPublished - 2018 Nov

    Bibliographical note

    Publisher Copyright:
    © 2018 Korean Society of Gastrointestinal Endoscopy.


    • Artificial intelligence
    • Capsule endoscopy
    • Deep learning
    • Lesion detection

    ASJC Scopus subject areas

    • Medicine (miscellaneous)
    • Radiology Nuclear Medicine and imaging
    • Gastroenterology


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