Steatotic liver index: An interpretable predictor of steatotic liver disease using machine learning with an enhanced shrinkage method
We developed SLI, a novel interpretable and parsimonious index for diagnosing SLD, which demonstrates superior predictive capability compared with FLI. Further studies are necessary to validate the diagnostic ability outside Japan.
Authors
- Satoko Yamaguchi (ORCID: https://orcid.org/0000-0003-2822-2281)
- Koji Oba (ORCID: https://orcid.org/0000-0001-5468-8988)
- Akira Okada (ORCID: https://orcid.org/0000-0001-6480-3388)
- Yasuhiro Hagiwara (ORCID: https://orcid.org/0000-0003-3792-5368)
- Toshimasa Yamauchi (ORCID: https://orcid.org/0000-0003-4827-6404)
- Masaomi Nangaku (ORCID: https://orcid.org/0000-0001-7401-2934)
- Nobuaki Michihata (ORCID: https://orcid.org/0000-0003-3091-114X)
- Kayo Ikeda Kurakawa
- Takeshi Kimura (ORCID: https://orcid.org/0000-0002-9344-4764)
- Sachiko Ono (ORCID: https://orcid.org/0000-0003-4378-2578)
- Takashi Kadowaki
- Yutaka Matsuyama (ORCID: https://orcid.org/0000-0003-2009-6831)
Institutions
- St. Luke's International Hospital (JP)
- Chiba Cancer Center (JP)
- Toranomon Hospital (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Hepatology Research
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1111/hepr.14156
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Okinaka Memorial Institute for Medical Research