Chen, S.-C.; Wu, G.-T.; Li, H.; Zhang, X.; Li, Z.-H.; Wong, P.-M.; Han, L.-F.; Qin, J.; Lo, K.-C.; Yeung, W.-F.;
et al. Feature Selection and Prediction of Pediatric Tuina in Attention Deficit/Hyperactivity Disorder Management: A Machine Learning Approach Based on Parent-Reported Children’s Constitution. Bioengineering 2025, 12, 1012.
https://doi.org/10.3390/bioengineering12101012
AMA Style
Chen S-C, Wu G-T, Li H, Zhang X, Li Z-H, Wong P-M, Han L-F, Qin J, Lo K-C, Yeung W-F,
et al. Feature Selection and Prediction of Pediatric Tuina in Attention Deficit/Hyperactivity Disorder Management: A Machine Learning Approach Based on Parent-Reported Children’s Constitution. Bioengineering. 2025; 12(10):1012.
https://doi.org/10.3390/bioengineering12101012
Chicago/Turabian Style
Chen, Shu-Cheng, Guo-Tao Wu, Han Li, Xuan Zhang, Zi-Han Li, Pong-Ming Wong, Le-Fei Han, Jing Qin, Kwai-Ching Lo, Wing-Fai Yeung,
and et al. 2025. "Feature Selection and Prediction of Pediatric Tuina in Attention Deficit/Hyperactivity Disorder Management: A Machine Learning Approach Based on Parent-Reported Children’s Constitution" Bioengineering 12, no. 10: 1012.
https://doi.org/10.3390/bioengineering12101012
APA Style
Chen, S.-C., Wu, G.-T., Li, H., Zhang, X., Li, Z.-H., Wong, P.-M., Han, L.-F., Qin, J., Lo, K.-C., Yeung, W.-F., & Ren, G.
(2025). Feature Selection and Prediction of Pediatric Tuina in Attention Deficit/Hyperactivity Disorder Management: A Machine Learning Approach Based on Parent-Reported Children’s Constitution. Bioengineering, 12(10), 1012.
https://doi.org/10.3390/bioengineering12101012
