Kenney Ng

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Kenney Ng, Ph.D.
Research Staff Member, Center for Computational Health; Manager, Health Analytics Research
IBM T.J. Watson Research Center

Kenney is a research staff member in the Center for Computational Health and manager of the Health Analytics Research Group at IBM Thomas J. Watson Research Center. His current research focus is on the development and application of data mining and machine learning techniques to analyze, model and derive insights from real world healthcare data. His prior research areas include information retrieval, probabilistic modeling, speech recognition, topic classification, and statistical language modeling. Before IBM Research, Kenney was a senior software engineer and architect in IBM Software Group for a number of products including IBM Patient Care and Insights (PCI), eDiscovery Analyzer (eDA), IBM Content Analyzer (ICA), Omnifind Yahoo! Edition (OYE), IBM Classification Module (ICM), and Omnifind Discovery Edition (ODE). Prior to IBM, Kenney was a principal software engineer at iPhrase Technologies and held research positions at the MIT Laboratory for Computer Science, BBN Technologies, and MIT Lincoln Laboratory. Kenney has Bachelors, Masters, and Ph.D. degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology.

Krause J, Perer A, Ng K, “Interacting with Predictions: Visual Inspection of Black-box Machine Learning Models”, ACM Conference on Human Factors in Computing Systems, 2016.

Ng K, Sun J, Hu J, Wang F, “Personalized Predictive Modeling and Risk Factor Identification using Patient Similarity”, American Medical Informatics Association (AMIA) Joint Summit on Translational Sciences, Translational Bioinformatics (TBI), 2014.

Wang Y, Ng K, Byrd R, Hu J, Ebadollahi S, Daar Z, deFilippi C, Steinhubl S, Stewart W, “Early detection of heart failure with varying prediction windows by structured and unstructured data in electronic health records”, EMBC 2015: 2530-2533

Ng K, Ghoting A, Steinhubl SR, Stewart WF, Malin B, Sun J., “PARAMO: a PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records”, J Biomed Inform. 2014 Apr;48:160-70.

Wang Y, Steinhubl SR, Defilippi, C, Ng K, Ebadollahi S, Stewart WF, Byrd RJ. “Prescription Extraction from Clinical Notes: Towards Automating EMR Medication Reconciliation”, AMIA 2015 Joint Summits on Translational Science, March 23-27, 2015, San Francisco, USA.

Vijayakrishnan R, Steinhubl SR, Ng K, Sun J, Byrd RJ, Daar Z, et al. “Prevalence of heart failure signs and symptoms in a large primary care population identified through the use of text and data mining of the electronic health record”, J Card Fail. 2014;20(7):459-64.