Explainable artificial intelligence for prediction of refractory ulcerative colitis: analysis of a Japanese Nationwide Registry
In this study, we constructed a highly accurate prognosis prediction model for UC, in which inflammation persists for an extensive period, by training a machine learning model for long-term disease progression. The results showed that machine learning can be used to determine the factors affecting remission during the treatment of refractory UC.
Authors
- Shota Nemoto (ORCID: https://orcid.org/0009-0004-3301-6807)
- Takashi Ueda (ORCID: https://orcid.org/0000-0001-7771-1407)
- Naoko Tomita
- Yasuhiro Miyake (ORCID: https://orcid.org/0000-0003-0095-0447)
- Yasuhiro Kanatani (ORCID: https://orcid.org/0000-0001-5790-4084)
- Masaya Sano (ORCID: https://orcid.org/0000-0002-0704-7042)
- Hidekazu Suzuki (ORCID: https://orcid.org/0000-0002-8994-6163)
Institutions
- Tokai University (JP)
- Hitachi (Japan) (JP)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1080/07853890.2025.2499960
- Citations
- 2
- Primary Topic
- Inflammatory Bowel Disease
- Type
- article
- Field-Weighted Citation Impact
- 3.63
Funders
- Japan Society for the Promotion of Science