論文發表
Google 學術搜尋
K. M. Kuo, Y. L. Lin, C. S. Chang* and T. J. Kuo, “An ensemble model for predicting dispositions of emergency department patients”, BMC Medical Informatics and Decision Making, https://doi.org/10.1186/s12911-024-02503-5, vol. 24, no. 105, 2024 (SCI) (Download) Yuntech
W. C. Hung, Y. L. Lin, C. W. Lin, W.L. Chin, and C. H. Wu*, “Advanced sampling technique in radiology Free-text data for efficiently building text mining models by deep learning in vertebral fracture”, Diagnostics, vol. 14, no. 2, p. 137, 2024 (SCI) (Download) Yuntech
W. C. Hung*,· Y. L. Lin, T. T. Cheng, W. L. Chin, L. T. Tu, C. K. Chen, C. H. Yang, C. H. Wu, “Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women,” Osteoporosis International, https://doi.org/10.1007/s00198-023-06913-5, 2024. (Download) (SCI) Yuntech
V. T. Tran, Y. L. Lin, and W. H. Tsai*, “Person identification using bronchial breath sounds recorded by mobile devices,” IEEE Access, DOI: 10.1109/ACCESS.2023.3279502, pp. 66122-66134 , 2023. (Download) (SCI) Yuntech
Y. L. Lin, K. Y. Lai, and W. Y. Chang*, “Skin medical image captioning using multi-label classification and Siamese network,” IEEE Access, DOI: 10.1109/ACCESS.2023.3249462, pp. 23447- 23454. 2023. (Download) (SCI) YunTech
Y. L. Lin, A. Huang, C. Y. Yang, and W. Y. Chang*, “Measurement of body surface area for psoriasis using u-net models,” Computational and Mathematical Methods in Medicine, vol. 2022, Article ID 7960151, 2022. (Download) (SCI) YunTech
W. C. Yeh*, Z. Hao, M. Forghani-elahabad, G. G. Wang, and Y. L. Lin, “Novel binary-addition tree algorithm for reliability evaluation of acyclic multistate information networks,” Reliability Engineering & System Safety, vol. 210, Article ID 107427, 2021. (Download) (SCI) YunTech
C. H. Chen, J. G. Hsieh, S. L. Cheng, Y. L. Lin, P. H. Lin, and J. H. Jeng, “Early short-term prediction of emergency department length of stay using natural language processing for low-acuity outpatients,” The American Journal of Emergency Medicine, vol. 38, no. 11, pp. 2368-2373, 2020. (Download) (SCI) ISU
C. H. Chen, J. G. Hsieh, S. L. Cheng, Y. L. Lin, P. H. Lin, and J. H. Jeng, “Emergency department disposition prediction using a deep neural network with integrated clinical narratives and structured data,” International Journal of Medical Informatics, vol. 139, Article ID 104146, 2020. (Download) (SCI) ISU
J. G. Hsieh, J. H. Jeng, Y. L. Lin, and Y. S. Kuo, “Single index fuzzy neural networks using locally weighted polynomial regression,” Fuzzy Sets and Systems,” vol. 368, pp.82-100, 2019. (Download) (SCI) ISU
Y. L. Lin, J. G. Hsieh, Y. S. Kuo, and J. H. Jeng, “NXOR-or XOR-based robust template decomposition for cellular neural networks implementing an arbitrary Boolean function via support vector classifiers,” Neural Computing and Applications, vol. 28, no. 1, pp. 299-311, 2017.(Download) (SCI) ISU
Y. L. Lin, J. G. Hsieh, J. H. Jeng, and W. C. Cheng, “On least trimmed squares neural networks,” Neurocomputing, vol. 161, pp. 107-112, 2015. (download) (SCI) ISU
Y. L. Lin, J. G. Hsieh, and J. H. Jeng, “Robust decomposition with guaranteed robustness for cellular neural networks implementing an arbitrary Boolean function,” Neurocomputing, vol. 143, pp. 339-346, 2014. (Download) (SCI) ISU
Y. L. Lin, “Least trimmed squares approach to Lucas-Kanade algorithm in object tracking problems,” Mathematical Problems in Engineering, vol. 2013 Article ID 324824, 2013. (Download) (SCI) ISU
H. K. Wu, Y. L. Lin, J. G. Hsieh, and J. H. Jeng, “Study on semiparametric Wilcoxon fuzzy neural networks,” Soft Computing, vol. 16, no. 1, pp. 11-21, 2012. (Download) (SCI) ISU
Y. L. Lin and W. L. Chen, “Fast Search Strategies for Fractal Image Compression,” Journal of Information Science & Engineering, Vol. 28, no. 1, 2012. (Download) (SCI) ISU
Y. L. Lin, and M. S. Wu, “An edge property-based neighborhood region search strategy for fractal image compression,” Computers & Mathematics with Applications, vol. 62 no. 1, pp. 310-318, 2011. (Download) (SCI) ISU
H. K. Wu, J. H. Hsieh, Y. L. Lin, and J. H. Jeng, “On maximum likelihood fuzzy neural networks,” Fuzzy Sets and Systems, vol. 161, no. 21, pp. 2795-2807, 2010. (Download) (SCI) ISU
Y. L. Lin, “Robust estimation of parameter for fractal inverse problem,” Computers & Mathematics with Applications, vol. 60, no. 7, pp. 2099-2108, 2010. (Download) (SCI) ISU
M. S. Wu, and Y. L. Lin, “Genetic algorithm with a hybrid select mechanism for fractal image compression,” Digital Signal Processing, vol. 20, no. 4, pp. 1150-1161, 2010. (Download) (SCI) ISU
J. G. Hsieh, Y. L. Lin*, and J. H. Jeng, “Preliminary study on Wilcoxon learning machines,” IEEE Transactions on Neural Networks, vol. 19, no. 2, pp. 201-211, 2008. (Download) (SCI) NSYSU
Y. L. Lin, W. D. Chang, and J. G. Hsieh, “A particle swarm optimization approach to nonlinear rational filter modeling,” Expert Systems with Applications, vol. 34, no. 2, pp. 1194-1199, 2008. (Download) (SCI) NSYSU
Y. L. Lin, J. G. Hsieh, and J. H. Jeng, “Robust template decomposition with restricted weights for cellular neural networks implementing an arbitrary Boolean function,” International Journal of Bifurcation and Chaos, vol. 17, no. 9, pp. 3151-3169, 2007. (Download) (SCI) NSYSU
Y. L. Lin, W. C. Teng, J. H. Jeng, and J. G. Hsieh, “Characterization of canonical robust template values for a class of uncoupled CNNs implementing linearly separable boolean functions,” WSEAS Transactions on Information Science and Applications, vol. 7, no. 2, pp. 940-944, 2005. (Download) NSYSU
H. M. Tzeng, Y. L. Lin, and J. G. Hsieh, “Forecasting violent behaviors for schizophrenic outpatients using their disease insights: Development of a binary logistic regression model and a support vector model,” International Journal of Mental Health, vol. 33, no. 2, pp. 17-31, 2004. (Download) NSYSU
H. M. Tzeng, J. G. Hsieh, and Y. L. Lin, “Predicting nurses' intention to quit with a support vector machine: a new approach to set up an early warning mechanism in human resource management,” CIN: Computers Informatics Nursing, vol. 22, no. 4, pp. 232-242, 2004. (Download) NSYSU