Machine learning for predicting CKD stages in patients with autosomal dominant polycystic kidney disease: a nationwide cohort study in Japan.
Saved in:
| Title: | Machine learning for predicting CKD stages in patients with autosomal dominant polycystic kidney disease: a nationwide cohort study in Japan. |
|---|---|
| Authors: | Shimada Y; Intelligent Systems Laboratory, SECOM CO., LTD., Tokyo, Japan.; Department of Infection Control Science, Juntendo University Graduate School of Medicine, Tokyo, Japan., Kataoka H; Department of Nephrology, Tokyo Women's Medical University, Tokyo, Japan., Nishio S; Department of Hemodialysis and Apheresis, Hokkaido University Hospital, Hokkaido, Japan., Hoshino J; Department of Nephrology, Tokyo Women's Medical University, Tokyo, Japan., Hiromura K; Department of Nephrology and Rheumatology, Gunma University Graduate School of Medicine, Gunma, Japan., Isaka Y; Department of Nephrology, Graduate School of Medicine, The University of Osaka, Osaka, Japan., Muto S; Department of Urology, Juntendo University Nerima Hospital, Tokyo, Japan. s-muto@juntendo.ac.jp. |
| Source: | Scientific reports [Sci Rep] 2026 Feb 13; Vol. 16 (1). Date of Electronic Publication: 2026 Feb 13. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2045-2322 |
|---|---|
| DOI: | 10.1038/s41598-026-39885-7 |
