Edakuni Nobutaka
Affiliate Master
Yamaguchi University
Novel Frailty Assessment Based on Multidimensional Physical Frailty Parameters Using Unsupervised Clustering in Respiratory Diseases: A Pilot Study
Journal of Clinical Medicine Volume 15 Issue 13
published_at 2026-07-01
Supplemental Data : https://public.oa.kenkyu.yamaguchi-u.ac.jp/9ba5ccfb-7f72-4169-a0e6-4a98a2c2d40a
Title
Novel Frailty Assessment Based on Multidimensional Physical Frailty Parameters Using Unsupervised Clustering in Respiratory Diseases: A Pilot Study
Creators
Fukatsu-Chikumoto Ayumi
Creators
Ohteru Yuichi
Creators
Utsunomiya Toshiaki
Source Identifiers
[EISSN] 2077-0383
Creator Keywords
frailty
machine learning
respiratory disease
Languages
eng
Resource Type
journal article
Publishers
MDPI
Date Issued
2026-07-01
Rights
© 2026 by the authors.()
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.()
Creative Commons Attribution 4.0 International(https://creativecommons.org/licenses/by/4.0/)
File Version
Version of Record
Access Rights
open access
Relations
[isIdenticalTo]
10.3390/jcm15135145
[isSupplementedBy]
[URI]https://public.oa.kenkyu.yamaguchi-u.ac.jp/9ba5ccfb-7f72-4169-a0e6-4a98a2c2d40a
Funding Refs
Japan Society for the Promotion of Science
[crossref_funder]https://doi.org/10.13039/501100001691
Award
Early detection of frailty and development of the pathophysiology management system in COPD
23K07628