Data Science Lab in NDMC circle image

Principal investigator Chin Lin Ph.D.

Present
2021/08-Recent Associate Professor, School of Medicine, National Defense Medical Center
2020/07-Recent Deputy Secretary-general, Aviation Medical Association R.O.C.
2019/07-Recent Deputy Dircetor, Medical Technology Education Center, National Defense Medical Center
2019/06-Recent Chief Technology Officer, Artificial Intelligence of Things center, Tri-Service General Hospital
2016/08-Recent Adjunct Assistant Professor, School of Public Health, National Defense Medical Center

Experience
2018/08-2021/07 Assistant Professor, Graduate Institute of Life Sciences, National Defense Medical Center
2017/07-2018/07 Postdoctoral Research Fellow, Department of Research and Development, National Defense Medical Center

I graduated from the PhD program in April 2016. The main expertise is to gain insight into data types and develop suitable algorithms. The main researches are to combine the modern deep learning technology and traditional statistics to apply on time series analysis, computer vision, natural language processing, etc. We are trying to construct an accurate computer-aided medical system in the medical field.

Researches Publications Get in touch Grants

Important news (Invited talks)


We shared our works to the world, which including the application of AI-ECG system in Tri-Services General Hospital, Taiwan.

Our AI research team won National Innovation Award

This project was selected as the "national best six" innovative star, and won an opportunity to speak at the conference. (related link)

Researches

We hope to improve the quality of medical services and reduce labor costs through algorithmic research, and empower the general public to use our researches. This laboratory has the computing resources including 12 NVIDIA® Tesla® V100. We provide an integrated development environment of RStudio Server Pro on our own server, you only need to connect with a browser without any local resources. Moreover, you also can develop web applications and publish to our Shiny Server.

Deep learning technology is developing from computer science, but the type of medical data is different from other fields. Statisticians have developed a lot of models for medical application, and our work is to combine statistics and deep learning technology to develop medical artificial intelligence.

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More than 90% diagnosis depends on medical images, but the medical image diagnosis is laborious and costly. An efficient computer-aided diagnosis system may decrease the extent of labor-intensive nature of health care. We are trying to improve the performance for clinical practice.

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The increase in the volume and accessibility of electronic medical data leads "big data" generation, but more than 80% information are hidden in unstructured data. Our lab is devoloping a series of algorithms for structurezizing free-text clinical narratives to further use them.

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Work with us


Current members:

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Chin Lin
Adviser

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Dung-Jang Tsai
Data scientist

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Yu-Sheng Luo
PhD student

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Jiunn-Harng Teng
PhD student

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Xin-An Lin
AI engineer

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Hai-Lun Huang
Data engineer

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Jiang-Cheng Jing
MS student

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Yu-Cheng Chen
Intern

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Hao-Chun Liao
Intern

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Pink Hsu
Assistant

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Hao-Wei Wang
Assistant


Pase members:

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Kai-Chieh Chen
MS

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Ying-Chu Chen
MS



We believe that having a diverse and inclusive team will help us to advance AI, for the betterment of human life. We value different viewpoints. All backgrounds, ideas, and perspectives are welcome.
By working with our group, you will:
Work on important problems in healthcare domain using AI.
Build and deploy machine learning / deep learning algorithms and applications.
Values:
Here are some values that we would like to see in you:
1. Hard work: We expect you to have a strong work ethic. We love our work and are passionate about the AI mission. We also value velocity, and like people that get things done quickly.
2. Flexibility: You should be willing to dive into different facets of a project. For example, besides developing machine learning algorithms, you may also need to work on data acquisition, conduct user interviews, or do frontend engineering. This may also require going outside your comfort zone, and learning to do new tasks in which you’re not an expert.
3. Learning: You should have a strong growth mindset, and want to learn continuously. This can involve reading books, taking coursework, talking to experts, or re-implementing research papers. We will also prioritize your learning and help point you in the right direction; but you need to put in the work to take advantage of this.
4. Teamwork: We work together in small teams. You are expected to support and collaborate with others; in turn you will also receive support from your teammates.
Prerequisites:
You should have a public health background or a software engineering background:
1. Public health background: You are professional in biostatistics and epidemiology, and like to learn programming. Previous ML/AI research experience would be a plus but is not required.
2. Software engineering background: We also encourage engineers without much AI background who are interested in developing ML applications to apply. Applicants should have made significant contributions to software projects in the past, for example through developing software systems at a company or through significant open source contributions.
Applying:
Please see below for how to apply to work with our group. The scholarship is only provided for students with outstanding performance at the related courses.
PhD students:
You should apply to graduate institute of life sciences at NDMC, and email us at xup6fup0629@gmail.com to arrange an interview time. The only acceptable research topic is algorithm development. We will provide a scholarship of NTD 28,000-45,000/mon accroding to your capability.
MS students:
You should apply to school of public health at NDMC, and participate our research projects in a co-directed way. We will provide a scholarship of NTD 8,000-20,000/mon accroding to the work content.
Other students:
We only provide the opportunity of internship without scholarship. Outside of coursework, we expect this to be your primary academic activity. As it takes time to familiarize oneself with a research project and to make significant contributions, we expect that students will be involved for at least one semester, with a strong preference for those who can potentially stay involved for the full year.
Engineer:
Currently, we only accept the data engineer with sufficient experience to apply our position, and there is no position for algorithm engineers. The salary is ranged NTD 650,000-900,000/year accroding to your position. We will evaluate your work performance to adjust your position and salary each quarter. Please email us xup6fup0629@gmail.com with your resume and two paragraphs on why you’d like to get involved.
Research assistant:
The research assistant don't need the programing background. The work content included general administration and IRB application. The full-time salary is ranged NTD 32,000-50,000/mon and the part-time salary is ranged NTD 10,000-20,000/mon accroding to your work content. Please email us xup6fup0629@gmail.com with your resume, a strong preference for those who want to be an engineer.