Predictive model development for possible sarcopenia in community-dwelling older adults: a cross-sectional machine learning approach using the Korean frailty and aging cohort study
Authors
Layoung Kim (ORCID: https://orcid.org/0000-0001-6772-5979)
Miji Kim (ORCID: https://orcid.org/0000-0002-0852-8825)
Gwang Suk Kim (ORCID: https://orcid.org/0000-0001-9823-6107)
Mo-Im Kim Nursing Research Institute, Yonsei University College of Medicine
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article
Predictive model development for possible sarcopenia in community-dwelling older adults: a cross-sectional machine learning approach using the Korean frailty and aging cohort study
Layoung Kim, Miji Kim, Gwang Suk Kim, Sooyoung Kwon et al.
Citations
1 citations
Journal
BMC Geriatrics
Topics
Nutrition and Health in Aging
Field-Weighted Citation Impact (FWCI)
1.16
article
Predictive model development for possible sarcopenia in community-dwelling older adults: a cross-sectional machine learning approach using the Korean frailty and aging cohort study
Layoung Kim, Miji Kim, Gwang Suk Kim, Sooyoung Kwon, Jae Young Chang, Chang Won Won, Namhee Kim
article en
1 citations
Abstract
No abstract available for this paper.
Publication Tag
BMC GeriatricsVol. 25(1)
Institutions
University of Suwon (KR), Yonsei University (KR), Kyung Hee University (KR), Kyung Hee University Medical Center (KR)
Funders
National Research Foundation, Yonsei University, Korea Health Industry Development Institute, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, College of Nursing, Yonsei University, Mo-Im Kim Nursing Research Institute, Yonsei University College of Medicine