Machine learning for morbid glomerular hypertrophy

Machine learning for morbid glomerular hypertrophy

Abstract A practical research method integrating data-driven machine learning with conventional model-driven statistics is sought after in medicine. Although glomerular hypertrophy (or a large renal corpuscle) on renal biopsy has pathophysiological implications, it is often misdiagnosed as adaptive/...

Full description

Bibliographic Details
Main Authors: Yusuke Ushio, Hiroshi Kataoka, Kazuhiro Iwadoh, Mamiko Ohara, Tomo Suzuki, Maiko Hirata, Shun Manabe, Keiko Kawachi, Taro Akihisa, Shiho Makabe, Masayo Sato, Naomi Iwasa, Rie Yoshida, Junichi Hoshino, Toshio Mochizuki, Ken Tsuchiya, Kosaku Nitta
Format: Article
Language:English
Published: Nature Portfolio 2022-11-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-23882-7

Internet

https://doi.org/10.1038/s41598-022-23882-7

Similar Items