| Literature DB >> 34209948 |
Dong Jun Oh1, Youngbae Hwang2, Yun Jeong Lim1.
Abstract
Small bowel capsule endoscopy (SBCE) is one of the most useful methods for diagnosing small bowel mucosal lesions. However, it takes a long time to interpret the capsule images. To solve this problem, artificial intelligence (AI) algorithms for SBCE readings are being actively studied. In this article, we analyzed several studies that applied AI algorithms to SBCE readings, such as automatic lesion detection, automatic classification of bowel cleanliness, and automatic compartmentalization of small bowels. In addition to automatic lesion detection using AI algorithms, a new direction of AI algorithms related to shorter reading times and improved lesion detection accuracy should be considered. Therefore, it is necessary to develop an integrated AI algorithm composed of algorithms with various functions in order to be used in clinical practice.Entities:
Keywords: artificial intelligence; automatic detection; capsule endoscopy; reading software
Year: 2021 PMID: 34209948 DOI: 10.3390/diagnostics11071183
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418