Wei-Chung Shia

Wei-Chung Shia

Adjunct Assistant Professor

My research work is the translational medical research of breast cancer. Through the application of information theory and bioinformatics technology, I analyze a large amount of data for a single topic and look forward to returning the research results to the clinic and making practical contributions to patients. Research topics in recent years include the following items: (1) Using the machine learning/deep learning strategies to identify image features of malignant tumor for mammography images and breast ultrasound images (2) Establishing a normal model of female breast density in Taiwan by analyzing mammography images, and discuss the correlation between breast density and breast cancer (3) The specific miRNAs in triple-negative breast cancer cell lines and their induction of apoptosis. In recent years, these research results were mainly published in international journals and clinical medical conferences. At the same time, I am also has been invited to many international breast medicine seminars for the lecture talk. Welcome to contact people who are interested in this field to exchange and share experiences.

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Education：

  • 逢甲大學 資訊工程學系 博士
  • 台中健康暨管理學院 生物資訊研究所 碩士
  • 真理大學 資訊科學系 學士

Research Interest：

  1. Wei-Chung Shia, Li-Sheng Lin, Dar-Ren Chen, "Classification of malignant tumours in breast ultrasound using unsupervised machine learning approaches," Scientific Reports, 11:1418, 2021-01. (SCIE)
  2. Weichung Shia, Dar-Ren Chen, "Classification of malignant tumors in breast ultrasound using a pretrained deep residual network model and support vector machine.," Computerized Medical Imaging and Graphics, Computerized Medical Imaging and Graphics 87 (2021) 101829, 2021-01. (SCIE)
  3. Dar-Ren Chen, Yao-Wen Chang, Hwa-Koon Wu, Wei-Chung Shia, Yu-Len Huang, "Multiview Contouring for Breast Tumor on Magnetic Resonance Imaging. Journal of digital imaging, Journal of digital imaging," Journal of Digital Imaging, Journal of Digital Imaging (2019) 32:713–727, 2019-03. (SCIE)
  4. Wei-Chung Shia, Hui-Ju Yang, Hwa-Koon Wu, Shih-Lung Lin, Hung-Wen Lai, Yu-Len Huang and Dar-Ren Chen, "Implant volume estimation in direct-to-implant breast reconstruction after nipple-sparing mastectomy.," J Surg Res., Journal of Surgical Research, 231: 290-296., 2018-11. (SCIE)
  5. Wei-Chung Shia, Hwa-Koon Wu, Yu-Len Huang, Li-Sheng Lin, Dar-Ren Chen, "Mammographic Density Distribution of Healthy Taiwanese Women and its Naturally Decreasing Trend with Age.," Scientific Reports, Scientific Reports, (2018) 8:14937., 2018-10. (SCIE)
  6. Shia, W. C., Huang, Y. L., Wu, H. K., & Chen, D. R., "Using Flow Characteristics in Three-Dimensional Power Doppler Ultrasound Imaging to Predict Complete Responses in Patients Undergoing Neoadjuvant Chemotherapy.," Journal of Ultrasound in Medicine, Journal of Ultrasound in Medicine, 36(5), 887-900., 2017-05. (SCIE)
  7. Shia, W. C., Chen, D. R., Huang, Y. L., Wu, H. K., & Kuo, S. J., "Effectiveness of evaluating tumor vascularization using 3D power Doppler ultrasound with high-definition flow technology in the prediction of the response to neoadjuvant chemotherapy for T2 breast cancer: a preliminary report.," Physics in medicine and biology, Physics in medicine and biology, 60(19), 7763., 2015-09. (SCIE)
  1. Weichung Shia, Darren Chen,"Using deep residual networks for malignant and benign classification of two-dimensional Doppler breast ultrasound imaging ," 2019 San Antonio Breast Cancer Symposium, Cancer Res February 15 2020 (80) (4 Supplement) P1-02-10; DOI: 10.1158/1538-7445.SABCS19-P1-02-10, 2019-12. Texas .
  2. W Shia, D Chen,"The comparison of mammographic density decreasing trend between Taiwanese healthy women and primary breast cancer patients. ," 16th St. Gallen International Breast Cancer Conference, The Breast. 44. S45. 10.1016/S0960-9776(19)30190-0., 2019-03. Vienna, Austria. .
  3. Wei-Chung Shia, Dar-Ren Chen,"Malignant and benign classification in power Doppler breast ultrasound imaging. ," 30th Anniversary AACR Special Conference on Convergence: Artificial Intelligence, Big Data, and Prediction in Cancer, 30th Anniversary AACR Special Conference on Convergence, 2018-10. Newport, RI, USA .
  4. W-C Shia, D-R Chen,"37P Association of mammographic density and fibroglandular tissue volume with the subtype of breast cancer. ," ESMO, Biomarkers Volume 28, Supplement 10, November 2017, 2017-11. 新加坡. .
  5. W. Shia, D. Chen,"The allele-specific copy number imbalance in CDK14/RABGAP1L/ SH3BP5L and the relation to the poor prognosis in breast cancer. ," 15th St.Gallen International Breast Cancer Conference, Cancer Res 2017;77, 2017-03. Vienna, Austria .
  6. W Shia and D Chen,"Abstract P1-04-10: Using the allele specific copy number profile to predict the poor prognosis breast cancer patients of Taiwanese. ," 2016 San Antonio Breast Cancer Symposium, Cancer Res 2017;77(4 Suppl):Abstractnr P1-04-10., 2016-12. San Antonio, Texas .
  1. 乳房植體體積估測裝置及其方法/發明/None/ None~None
Last update：2024-4-20, 9:05 a.m. Next update：2024-4-21, 9 a.m.