Artificial Intelligence Model for Time Series Classification: Prediction of Delayed Balloon Expulsion Test Using High‐Resolution Anorectal Manometry Data and Time‐Series Integrated Pressurized Volume
Our AI model accurately classified delayed BE test results using raw HRAM data and TS-IPVs of male and female patients with an AUC of 0.99. Furthermore, the model used time-variant HRAM pressure data and TS-IPVs throughout the push maneuver without any data loss; therefore, TS-IPV could be used as a more reliable marker than conventional parameters for classifying delayed BE test results.
Authors
- Kee Wook Jung (ORCID: https://orcid.org/0000-0002-3771-3691)
- Segyeong Joo (ORCID: https://orcid.org/0000-0002-1681-3845)
- Satish S.C. Rao (ORCID: https://orcid.org/0000-0002-4446-8452)
- Myeongsook Seo (ORCID: https://orcid.org/0000-0003-2564-7380)
- Kiwon Yoon
- Seung‐Jae Myung
Institutions
- Ulsan College (KR)
- Augusta University (US)
- Asan Medical Center (KR)
- University of Ulsan (KR)
- Gangneung Asan Hospital (KR)
Publication Details
- Journal
- Neurogastroenterology & Motility
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1111/nmo.70044
- Citations
- 1
- Primary Topic
- Gastrointestinal motility and disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.81
Funders
- National Research Foundation
- National Research Foundation of Korea
- Korean Society of Neurogastroenterology and Mobility
- Ministry of Science and ICT, South Korea