Responding to a super-aged society: A community-based model for early frailty detection using AI and smart meter data – Insights from Japan

Machiko Uenishi, Peipei Song

Open source

DOI: 10.35772/ghm.2025.01114
Published: 2025-12-31
Container: Global Health & Medicine
Publisher: National Center for Global Health and Medicine (JST)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.35772/ghm.2025.01114,
  title = {Responding to a super-aged society: A community-based model for early frailty detection using AI and smart meter data – Insights from Japan},
  author = {Machiko Uenishi and Peipei Song},
  year = {2025},
  journal = {Global Health \&amp; Medicine},
  doi = {10.35772/ghm.2025.01114},
  url = {https://doi.org/10.35772/ghm.2025.01114}
}

RIS

TY  - JOUR
TI  - Responding to a super-aged society: A community-based model for early frailty detection using AI and smart meter data – Insights from Japan
AU  - Machiko Uenishi
AU  - Peipei Song
PY  - 2025
JO  - Global Health &amp; Medicine
DO  - 10.35772/ghm.2025.01114
UR  - https://doi.org/10.35772/ghm.2025.01114
ER  -

APA

Uenishi, M., & Song, P. (2025). Responding to a super-aged society: A community-based model for early frailty detection using AI and smart meter data – Insights from Japan. Global Health & Medicine. https://doi.org/10.35772/ghm.2025.01114

Source records

crossref · retrieved 2026-09-27T11:47:56.759Z