A Hybrid Intelligent Classification System for Geriatric Frailty Syndrome Prevention and Control-Reference-Cited by-同舟云学术

A Hybrid Intelligent Classification System for Geriatric Frailty Syndrome Prevention and Control

Published:2024-01-26 Issue: Volume:33 Page:212-216
ISSN:
Container-title:Proceedings of the 2024 4th International Conference on Bioinformatics and Intelligent Computing
language:
Short-container-title:

Author:

Cai Chengyi¹^ORCID,Liu Hui¹^ORCID,Chen Xujiao²^ORCID,Li Yanfei³^ORCID

Affiliation:

1. Institute of Artificial Intelligence & Robotics (IAIR), Key Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic and Transportation Engineering, Central South University, China

2. Department of Geriatrics, Zhejiang Provincial Hospital of Chinese Medicine, China

3. School of Mechatronic Engineering, unan Agricultural University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3665689.3665725

Reference10 articles.

1. Resistance training for older adults: position statement from the national strength and conditioning association;Fragala M. S.;The Journal of Strength & Conditioning Research,2019

2. Dynamic Analysis of the Effects of Aging on China's Sustainable Economic Growth;Zhang M.;Sustainability,2023

3. Screening, diagnosis and management of sarcopenia and frailty in hospitalized older adults: recommendations from the Australian and New Zealand Society for Sarcopenia and Frailty Research (ANZSSFR) Expert Working Group;Daly R. M.;The Journal of Nutrition, Health & Aging,2022

4. Utilizing multimodal approach to identify candidate pathways and biomarkers and predicting frailty syndrome in individuals from UK Biobank;Tseng W. H.-S.;GeroScience,2023

5. Importance analysis of psychosociological variables in frailty syndrome in heart failure patients using machine learning approach;Pasieczna A. H.;Scientific Reports,2023