Education
Postdoctoral Scientist Biomedical Informatics Columbia University New York
Ph D Computer Science Belfast, UK Queen’s University
MS Software Engineering Xidian University China
BS Electronic Engineering Xidian University China
Speaker Topics
- Health Big Data and Predictive Analysis
- Natural Language Processing
- Health Informatics and Management
- Text Mining and Information Extraction
- Artificial Intelligence and machine learning
Interests & Expertise
Jake Luo’s research interest lies in data-driven predictive analysis using machine learning-based algorithms and technologies, such as data mining, natural language processing and knowledge representation and modelling. He is interested in investigating how these computing technologies can be used to improve health care by providing intelligent decision support for clinicians, medical researchers, patients, and policymakers.
Luo’s active research programs involve developing innovative heath data science technologies for knowledge discovery, adapting machine learning algorithms to enhance clinical data processing, implementing collaborative team science initiatives to improve health services and research, and creating intelligent clinical informatics tools to support evidence-based decision making.
Selected Publications
Chesley, N. A., Meier, H., Luo, J., Apchemengich, I., & Davies, W. (2020, June).
Social factors shaing the adoption of lead-filering point-of-use systems: an observational study of an MTurk sample. Journal of Water and Health.
Lu, Q., Zhou, S., Tao, F., Luo, J., & Wang, Z. (2020).
Enhancing Gene Expression Programming based on Space Partition and Jump for Symbolic Regression. Information Sciences,
547, 553-567.
Zolnoori, M., Fung, K. W., Patrick, T. B., Fontelo, P., Kharrazi, H., Faiola, A., Shirley Wu, Y. S., Eldredge, C. E., Luo, J., Conway, M., Zhu, J., Park, S. K., Xu, K., & Moayyed, H. (2019, March).
The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications. Data in Brief, 103838.
Barzekar, H., Ebrahimzadeh, F., Luo, J., Karami, M., Robati, Z., & Goodarzi, P. (2019).
Adoption of Hospital Information System Among Nurses: a Technology Acceptance Model Approach. Acta Informatica Medica,
27(5), 305.
Benson, L. C., Cobb, S. C., Hyngstrom, A. S., Keenan, K. G., Luo, J., & O’Connor, K. M. (2019, April (2nd Quarter/Spring)).
A Principal Components Analysis Approach to Quantifying Foot Clearance and Foot Clearance Variability. Journal of Applied Biomechanics,
35(2), 116-122.
Zolnoori, M., Wah Fung, K., Patrick, T. B., Fontelo, P., Kharrazi, H., Faiola, A., Shuan Shirley Wu, Y., Eldredge, C. E., Luo, J., Conway, M., Zhu, J., Kyung Park, S., Xu, K., Moayyed, H., & Goudarzvand, S. (2019, January (1st Quarter/Winter)).
A Systematic Approach for Developing a Corpus of Patient Reported Adverse Drug Events: A Case Study for SSRI and SNRI Medications. Journal of biomedical informatics.
Benson, L. C., Cobb, S. C., Hyngstrom, A. S., Keenan, K. G., Luo, J., & O’Connor, K. M. (2018, December).
Identifying trippers and non-trippers based on knee kinematics during obstacle-free walking. Human Movement Science,
62, 58-66.
Zhao, Y., Fesharaki, N. J., Li, X., Patrick, T. B., & Luo, J. (2018, April (2nd Quarter/Spring)).
Semantic-Enhanced Query Expansion System for Retrieving Medical Image Notes. Journal of Medical Systems,
42(6), 105.
Honors & Awards
Outstanding Clinical Research Informatics Paper Award Nominated (2014) AMIA.
Outstanding Reviewer Award (2013) MedInfo 2013.
Top hottest 25 paper (2012) Journal of Biomedical Informatics.
Distinguished paper award (2011) AMIA CRI summit.
Professional Memberships
- Member of the American Medical Informatics Association (AMIA), 2009-present
- Member of Association for Advancement of Artificial Intelligence (AAAI), 2006-2010
- Member of Institute of Electrical and Electronics Engineers (IEEE), 2008-2009
Courses Taught
- Health Big Data Processing
- Introduction to Health Care Informatics
- Biomedical Informatics Seminar
- Fundamental Programming
- Advanced Programming
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