Li-Chin Chen

Assistant Research Fellow
Data Analytics and Digital Transformation Research Center
National Taiwan University
email logo lichinc (at) ntu.edu.tw
ORCID logo https://orcid.org/0000-0002-2122-1625

Research Interests

Awards and Honors

  1. Xin-Miao Zhuo Information Student Leadership Award, 2010. Institute of Information and Computer Machinery, Taiwan.

  2. President Educational Award, 2011. Ministry of Education, Taiwan.

  3. Graduate Student Outstanding Paper Award: International Journal Papers, 2014. Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taiwan.

  4. Best Ph.D. dissertation awards, 2014. Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taiwan.

  5. Academic Research Category, 17th National Innovation Awards, 2020. Research Center for Biotechnology and Medicine, Taiwan.

  6. Golden Award, Youth Creative Proposal Competition-AI and Big Data Category, 2023. Clinical Innovation Center, Taipei Verterans General Hospital, Taiwan.

Projects

Constructing a General Demographic and Disease Distribution Foundational Model Based on Deep Learning Technology

Following the robust advancement of deep learning methodologies and foundational models, the field has attained significant results across a myriad of applications, proving advantageous for augmenting machine learning outcomes without dependence on artificial feature extraction. Nevertheless, there has been limited adoption of these technologies within the realm of public health. One contributing factor is that a substantial portion of public health, medical, and governmental data is predominantly presented in tabular format, which currently lacks effective pre-trained or foundational models tailored for this domain. Moreover, existing models are not designed to support public health initiatives. Public health policies are formulated based on the prevailing population dynamics and disease distribution; thus, it is imperative to leverage the extensive repository of accumulated data alongside the capabilities of deep learning methods to facilitate industry transformation and inform public health policy development.