Conferences

  • Jie W., Ronald M., Yao X., Rishikesan K. Improving Sepsis Prediction Model Generalization With Optimal Transport. Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:474-488, 2022.

  • A.I. Wong, R. Kamaleswaran, A. Tabaie, M. Reyna, C. Josef, C. Robichaux, A. de Hond, EW. Steyerberg, AL. Holder, S. Nemati, TG Buchman, JM Blum. “Prediction of Acute Respiratory Failure requiring advanced respiratory support in Advance of Interventions and Treatment (PARFAIT): A multivariable prediction model from electronic medical record data”, Critical Care Explorations 2021.

  • Bennett TD, Moffitt RA, Hajagos JG, et al. Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative. JAMA Netw Open. 2021;4(7):e2116901. doi:10.1001/jamanetworkopen.2021.16901

  • Steinberg R, Anderson B, Hu Z, Johnson TM, O'Keefe JB, Plantinga LC, Kamaleswaran R, Anderson B. Associations between remote patient monitoring programme responsiveness and clinical outcomes for patients with COVID-19. BMJ Open Qual. 2021 Sep;10(3):e001496. doi: 10.1136/bmjoq-2021-001496. PMID: 34518302; PMCID: PMC8438571.

  • Wong, A. K. I., Charpignon, M., Kim, H., Josef, C., de Hond, A. A., Fojas, J. J., ... & Celi, L. A. (2021). Analysis of Discrepancies Between Pulse Oximetry and Arterial Oxygen Saturation Measurements by Race and Ethnicity and Association With Organ Dysfunction and Mortality. JAMA network open, 4(11), e2131674-e2131674.

  • Zhou, A., Raheem, B. and Kamaleswaran, R., OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection. IEEE/ACM transactions on computational biology and bioinformatics.

  • S. Srinivasan, E. Begoli, G. Peterson, M. Muthiah, and R. Kamaleswaran, Markers in Unstructured Progress Notes Predict Imminent ICU Admission Using Machine Learning, SCCM 2020

  • R. Swaminathan, A. Singh, A. Mohammed, and R. Kamaleswaran, Machine Learning Predicts Early Onset of Sepsis from Continuous Physiological Data of Critically Ill Adults. IEEE-NIH HI-POCT 2019

  • K. Silvas, J. O'Neill, B. Monk, R. Schorr, R. Kamaleswaran 114 Emergency Department Factors Associated With Early Rapid Responses Activation After Admission. Annals of Emergency Medicine. 2019 Oct 1;74(4):S46.

  • R. Kamaleswaran, C. Koo, R. Helmick, V. Mas, J. Eason, D. Maluf. Predicting Early Post-Operative Sepsis in Liver Transplantation Applying Artificial Intelligence. ILTS 2019, 25th Annual International Congress (Plenary Abstract Presentation)

  • L.K. Chinthala, A. Mohammed, and R. Kamaleswaran. ICUWaveDB: A Big Data Approach to Capture and Processing Real-Time Streams in Critical Care. AMIA 2019 Clinical Informatics Conference. Atlanta, GA.

  • R. Kamaleswaran, R. Mahajan, O. Akbilgic, N.I. Shafi, R.L. Davis. 46: Machine Learning Applied To Continuous Physiologic Data Predicts Fever In Critically Ill Children. Critical Care Medicine 47, no. 1 (2019): 23. Star Research Achievement Award (Top 64 of 1831 Abstracts)

  • R. Mahajan, R. Kamaleswaran, O. Akbilgic, “A hybrid feature extraction method to detect Atrial Fibrillation from single lead ECG recording”. IEEE BHI 2018 doi:10.1109/BHI.2018.8333383

  • F. Van Wyk, A. Khojandi, R. Kamaleswaran, O. Akbilgic, S. Nemati, R.L. Davis, “How Much Data Should We Collect? A Case Study in Sepsis Detection Using Deep Learning” IEEE-NIH HI-POCT 2017

  • R. Kamaleswaran, O. Akbilgic, M. Hallman, A. West, R.L. Davis, S. Shah, “Physiomarker Variability For Early Prediction of Severe Sepsis in the Pediatric Intensive Care Unit” SCCM 2018 Critical Care Congress, San Antonio, TX

  • R. Mahajan, R. Kamaleswaran and O. Akbilgic, “Cardiac Rhythm Classification from a Short Single Lead ECG Recording via Random Forests” Computing in Cardiology 2017 Rennes, France.

  • R. Mahajan, R. Kamaleswaran and O. Akbilgic, “Effects of varying sampling frequency on the analysis of continuous ECG data streams” in the Third International Workshop on Data Management and Analytics for Medicine and Healthcare, September 2017.

  • R. Mahajan, R. Kamaleswaran and O. Akbilgic, “Paroxysmal Atrial Fibrillation Screening at Different ECG Sampling Frequencies via Symbolic Pattern Recognition”, in Proc. Of IEEE Biomedical and Health Informatics (BHI), 2017

  • R. Kamaleswaran, C. Collins, A. James, and C. McGregor, “CoRAD: Visual Analytics for Cohort Analysis,” in IEEE International Conference on Healthcare Informatics 2016 (ICHI 2016), 2016, pp. 517–526. doi: 10.1109/ICHI.2016.93

  • R. Kamaleswaran, J. E. Pugh, A. Thommandram, A. James, and C. Mcgregor, “Visualizing Neonatal Spells: Temporal Visualization of High Frequency Cardiorespiratory Physiological Event Streams,” in Proc. of IEEE VIS 2014 Workshop on Visualization of Electronic Health Records, 2014.

  • R. Kamaleswaran and C. McGregor, “A Real-Time Multi-dimensional Visualization Framework for Critical and Complex Environments,” in Computer-Based Medical Systems (CBMS), 2014 IEEE 27th International Symposium on, 2014, pp. 325–328.

  • J. Sritharan, R. Kamaleswaran, K. McFarlan, M. Lemonde, C. George, and O. Sanchez, “Assessing the environmental factors in two Ontario communities with diverging colorectal cancer incidence rates.,” Cancer Res., vol. 73, no. 8 Supplement, p. 4819 LP-4819, Nov. 2014.

  • R. Kamaleswaran, A. Thommandram, Q. Zhou, M. Eklund, Y. Cao, W. P. Wang, and C. McGregor, “Cloud framework for real-time synchronous physiological streams to support rural and remote Critical Care,” in Computer-Based Medical Systems (CBMS), 2013 IEEE 26th International Symposium on, 2013, pp. 473–476.

  • C. Tomlinson, M. Rafii, R. Kamaleswaran, R. Ball, P. Pencharz. (2012). Fractional synthesis rate of creatine from arginine in healthy adult men. 2012 Research Meeting, FASEB J.

  • R. Kamaleswaran, C. McGregor. (2012). CBPSP: Complex Business Processes For Stream Processing. 25th Canadian Conference on Electrical and Computer Engineering (CCECE)

  • R. Kamaleswaran, C. McGregor, A. James. (2012). A novel framework for event stream processing of clinical practice guidelines. Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on

  • R. Kamaleswaran, M. Eklund. (2011). A method for interactive hypothesis testing for clinical decision support systems using Ptolemy II. Electrical and Computer Engineering (CCECE), 2011 24th Canadian Conference

  • J. Percival, C. McGregor, N. Percival, R. Kamaleswaran, S. Tuuha. (2010). A framework for nursing documentation enabling integration with HER and real-time patient monitoring. Computer-Based Medical Systems (CBMS), 2010 IEEE 23rd International Symposium on

  • R. Kamaleswaran, C. McGregor, J. M. Eklund, J. Mikael, R. Kamaleswaran, C. McGregor, and J. M. Eklund, “A method for clinical and physiological event stream processing,” in Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE, 2010, vol. 1, pp. 1170–1173.

  • M. Blount, C. McGregor, A. James, D. Sow, R. Kamaleswaran, S. Tuuha, J. Percival, N. Percival. (2010). On the integration of an artifact system and a real-time healthcare analytics system. 1st ACM International Health Informatics Symposium

  • R. Kamaleswaran, C. McGregor, J. Percival. (2009). Service oriented architecture for the integration of clinical and physiological data for real-time event stream processing. Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE