PAPERS
- Stratified Locality-Sensitive Hashing for Sublinear Time Critical Event Prediction, Y. Bryce Kim, Erik Hemberg, and Una-May O'Reilly. Conference on Neural Information Processing Systems (NIPS) Machine Learning in Healthcare Workshop, 2016. Best Paper Award.
- Analysis of Locality-Sensitive Hashing for Fast Critical Event Prediction on Physiological Time Series, Y. Bryce Kim and Una-May O'Reilly. 38th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2016.
- Stratified Locality-Sensitive Hashing for Accelerate Physiological Time-Series Retrieval, Y. Bryce Kim, Erik Hemberg, and Una-May O'Reilly. 38th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2016.
- Analysis of Data-Driven Event Prediction based on Sublinear Time Retrieval of Physiological Waveforms, Y. Bryce Kim and Una-May O'Reilly. Conference on Neural Information Processing Systems (NIPS) Machine Learning in Healthcare Workshop, 2015.
- Large-Scale Physiological Waveform Retrieval via Locality-Sensitive Hashing, Y. Bryce Kim and Una-May O'Reilly. 37th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015.
- Large-Scale Prediction of Acute Hypotensive Episodes via Locality-Sensitive Hashing on Physiological Waveform Time Series , Y. Bryce Kim and Una-May O'Reilly. 37th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015.
- Gaussian Process-based Feature Selection for Wavelet Parameters: Predicting Acute Hypotensive Episodes from Physiological Signals, Franck Dernoncourt, Kalyan Veeramachaneni and Una-May O'Reilly. IEEE 28th International Symposium on Computer-Based Medical Systems. IEEE Computer Society, 2015.
- BeatDB: An end-to-end approach to unveil saliencies from massive signal data sets, Franck Dernoncourt, S.M, thesis, MIT Dept of EECS, February 2015. Advisors: Una-May O'Reilly, Kalyan Veeramachaneni.
- Large-Scale Methodological Comparison of Acute Hypotensive Episode Forecasting Using MIMIC2 Physiological Waveforms, Y. Bryce Kim, Joohyun Seo, Una-May O'Reilly, 2014 Proceedings of the IEEE 27th International Symposium on Computer-Based Medical Systems (CBMS), New York, May 2014.
- PhysioMiner: A Scalable Cloud Based Framework for Physiological Waveform Mining, Vineet Gopal, M.Eng Thesis completed in MIT Dept of EECS, 2014.
- Learning Decision Lists with Lags for Physiological Time Series, Erik Hemberg, Kalyan Veeramachaneni, Babak Hodjat, Prashan Wanigasekara, Hormoz Shahrzad, Una-May O'Reilly, 3rd Workshop on Data Mining for Medicine and Healthcare (2014), April 26, 2014, Philadelphia, PA, (held in conjunction with 14th SIAM International Conference on Data Mining (SDM 2014).
- beatDB : A Large Scale Waveform Feature Repository, Franck Dernoncourt, Kalyan Veeramachaneni and Una-May O'Reilly, MLCDA@NIPS 2013 : Machine Learning for Clinical Data Analysis and Healthcare.
- Efficient Training Set Use For Blood Pressure Prediction in a Large Scale Learning Classifier System, Erik Hemberg, Kalyan Veeramachaneni, Franck Dernoncourt, Mark Wagy and Una-May O'Reilly, Sixteenth International Workshop on Learning Classifiers Systems.
- Learning Blood Pressure Behavior from Large Physiological Waveform Repositories, Alexander Waldin, Kalyan Veeramachaneni, Una-May O'Reilly, ICML Workshop on Healthcare 2013.
- Large-scale Consensus Clustering and Data Ownership Considerations for Medical Applications, Chidube Ezeozue, S.M, thesis, MIT Dept of EECS, 2013. Advisors: Una-May O'Reilly, Kalyan Veeramachaneni.
- Learning Blood Pressure Behavior from Large Blood Pressure Waverform Repositories and Building Predictive Models, Alexander Waldin, Masters Thesis, ETH-Zurich, 2013. Advisors: Kalyan Veeramachaneni, Una-May O'Reilly.
