Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43815, first published .
A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study

A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study

A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study

Journals

  1. Li Y, Ma J, Xiao J, Wang Y, He W. Use of extreme gradient boosting, light gradient boosting machine, and deep neural networks to evaluate the activity stage of extraocular muscles in thyroid-associated ophthalmopathy. Graefe's Archive for Clinical and Experimental Ophthalmology 2024;262(1):203 View
  2. Lee J, Lee S. Identification of Risk Groups for and Factors Affecting Metabolic Syndrome in South Korean Single-Person Households Using Latent Class Analysis and Machine Learning Techniques: Secondary Analysis Study. JMIR Formative Research 2023;7:e42756 View
  3. Guo M, Xu S, He X, He J, Yang H, Zhang L. Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health. Frontiers in Public Health 2024;12 View
  4. Liu F, Zang Y, Feng L, Shi X, Wu W, Liu X, Song Y, Xu J, Gui S, Chen X. Concomitant Prediction of the Ki67 and PIT-1 Expression in Pituitary Adenoma Using Different Radiomics Models. Journal of Imaging Informatics in Medicine 2024 View
  5. Zhu H, Liu L, Liang S, Ma C, Chang Y, Zhang L, Fu X, Song Y, Zhang J, Zhang Y, Jiang C. Rupture risk assessment in cerebral arteriovenous malformations: an ensemble model using hemodynamic and morphological features. Journal of NeuroInterventional Surgery 2024:jnis-2024-022208 View