Published on in Vol 22, No 1 (2020): January
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/12509, first published
.
![Classification and Regression Tree and Computer Adaptive Testing in Cardiac Rehabilitation: Instrument Validation Study Classification and Regression Tree and Computer Adaptive Testing in Cardiac Rehabilitation: Instrument Validation Study](https://asset.jmir.pub/assets/d333ef763632441f3d5bf2f0b2fb9787.png 480w,https://asset.jmir.pub/assets/d333ef763632441f3d5bf2f0b2fb9787.png 960w,https://asset.jmir.pub/assets/d333ef763632441f3d5bf2f0b2fb9787.png 1920w,https://asset.jmir.pub/assets/d333ef763632441f3d5bf2f0b2fb9787.png 2500w)
Journals
- Yu C, Lin Y, Lin C, Lin S, Wu J, Chang S. Development of an Online Health Care Assessment for Preventive Medicine: A Machine Learning Approach. Journal of Medical Internet Research 2020;22(6):e18585 View
- Tennant A, Küçükdeveci A. Application of the Rasch measurement model in rehabilitation research and practice: early developments, current practice, and future challenges. Frontiers in Rehabilitation Sciences 2023;4 View
- Zhou J, Zha F, Liu F, Wan L, Zhou M, Long J, Chen M, Xue K, Wang Y. Reliability and validity of a graphical computerized adaptive test Longshi scale for rapid assessment of activities of daily living in stroke survivors. Scientific Reports 2024;14(1) View
- Sheng B, Zhang S, Gao Y, Xia S, Zhu Y, Yan J. Elucidating the influence of familial interactions on geriatric depression: A comprehensive nationwide multi-center investigation leveraging machine learning. Acta Psychologica 2024;246:104274 View