Publications

M. K. Mutnuri, H. T. Stelfox, N. D. Forkert, and J. Lee. Using domain adaptation and inductive transfer learning to improve patient outcome prediction in the intensive care unit: retrospective observational study. Journal of Medical Internet Research, 26:e52730, August 2024.

P. Ghasemi and J. Lee. Unsupervised feature selection to identify important ICD-10 and ATC codes for machine learning on a cohort of patients with coronary heart disease: retrospective study. JMIR Medical Informatics, 12:e52896, July 2024.

H. Kwon, M. Greenberg, C. B. Josephson, and J. Lee. Measuring the prediction difficulty of individual cases in a dataset using machine learning. Scientific Reports, 14:10474, May 2024.

S. Lee, A. A. Shaheen, D. J. T. Campbell, C. Naugler, J. Jiang, R. L. Walker, H. Quan, and J. Lee. Evaluating the coding accuracy of type 2 diabetes mellitus among patients with non-alcoholic fatty liver disease. BMC Health Services Research, 24:218, February 2024.

A. Amson, E. Pauze, T. Ramsay, V. Welch, J. S. Hamid, J. Lee, D. L. Olstad, C. Mah, K. Raine, and M. Potvin Kent. Examining gender differences in adolescent exposure to food and beverage marketing through go-along interviews. Appetite, 193:107153, February 2024.

A. Harper, F. Schulte, G. M. T. Guilcher, T. H. Truong, K. Reynolds, M. Spavor, N. Logie, J. Lee, and M. M. Fidler-Benaoudia. Alberta childhood cancer survivorship research program. Cancers, 5(15):3932, August 2023.

C. E. Valderrama, D. L. Olstad, Y. Y. Lee, and J. Lee. Identifying factors that shape whether digital food marketing appeals to children. Public Health Nutrition, 26(6):1125-1142, April 2023.

F. R. Lucini, H. T. Stelfox, and J. Lee. Deep learning-based recurrent delirium prediction in critically ill patients. Critical Care Medicine, 51(4):492-502, April 2023.

B. Bajgain, D. Lorenzetti, J. Lee, and K. Sauro. Determinants of implementing artificial intelligence-based clinical decision support tools in healthcare: a scoping review protocol. BMJ Open, 13:e068373, February 2023.

H. T. Stelfox, S. M. Bagshaw, J. Lee, and K. M. Fiest. A call to measure family presence in the adult intensive care unit. Intensive Care Medicine, 48(11):1665-1666, September 2022.

A. K. Cornhill, S. Dykstra, A. Satriano, D. Labib, Y. Mikami, J. Flewitt, E. Prosio, S. Rivest, R. Sandonato, A. G. Howarth, C. Lydell, C. A. Eastwood, H. Quan, N. Fine, J. Lee, and J. A. White. Machine learning patient-specific prediction of heart failure hospitalization  using cardiac MRI-based phenotype and electronic health information. Frontiers in Cardiovascular Medicine, 9:890904, June 2022.

C. E. Valderrama, D. J. Niven, H. T. Stelfox, and J. Lee. Predicting abnormal laboratory blood test results in the intensive care unit using novel features based on information theory and historical conditional probability: observational study. JMIR Medical Informatics, 10(6):e35250, June 2022.

The ICU Family Presence Investigators. Family presence in adult intensive care units. Intensive Care Medicine, 48(6):759–761, June  2022.

Z. Shakeri Hossein Abad, G. P. Butler, W. Thompson, and J. Lee. Physical activity, sedentary behaviour, and sleep on Twitter: multicountry and fully labeled public dataset for digital public health surveillance research. JMIR Public Health and Surveillance, 8(2):e32355, February 2022.

Z. Shakeri Hossein Abad, G. P. Butler, W. Thompson, and J. Lee. Crowdsourcing for machine learning in public health surveillance: lessons learned from Amazon Mechanical Turk. Journal of Medical Internet Research, 24(1):e28749, January 2022.

B. Kim, P. Ghasemi, P. Stolee, and J. Lee. Clinicians and older adults’ perceptions of the utility ofpatient generated health data in caring for older adults: an exploratory mixed-methods study. JMIR Aging, 4(4):e29788, November 2021.

S. Aponte-Hao, S. T. Wong, M. Thandi, P. Ronksley, K. McBrien, J. Lee, M. Grandy, D. Mangin, A.Katz, A. Singer, D. Manca, and T. Williamson. Machine learning for identification of frailty in Canadian primary care practices. International Journal of Population Data Science, 6(1):11, September 2021.

G. Geri, L. Ferrer, N. Tran, L. A. Celi, M. Jamme, J. Lee, and A. Vieillard-Baron. Cardio-pulmonary-renal interactions in ICU patients. Role of mechanical ventilation, venous congestion and perfusion deficiton worsening of renal function: insights from the MIMIC-III database. Journal of Critical Care, 64:100-107, August 2021.

S. Lee, B. Li, E. A. Martin, A. D'Souza, J. Jiang, C. Doktorchik, D. A. Southern, J. Lee, N. Wiebe, H. Quan, and C. Eastwood.  CREATE: a new data resource to support cardiac precision health. CJC Open, 3(5):639-645, May 2021.

D. Labib, S. Dykstra, Z. Slavikova, Y. Mikami, K. Yee, J. Flewitt, M. Seib, S. Rivest, R. Sandonato, A. Satriano, B. Heydari, A. Howarth, C. Lydell, P. D. Faris, E. Pituskin, W. Y. Cheung, J. Lee, and J. White. Effect of active cancer on the cardiac phenotype: a cardiac magnetic resonance imaging‐based study of myocardial tissue health and deformation in patients with chemotherapy‐naïve cancer. Journal of the American Heart Association, 10(9):e019811, May 2021.

Z. Shakeri Hossein Abad, D. M. Maslove, and J. Lee. Predicting discharge destination of critically ill patients using machine learning. IEEE Journal of Biomedical and Health Informatics, 25(3):827-837, March 2021.

Z. Shakeri Hossein Abad, A. Kline, M. Sultana, M. Noaeen, E. Nurmambetova, F. Lucini, M. Al-Jefri, and J. Lee. Digital public health surveillance: a systematic scoping review. npj Digit Medicine, 4(1):41, March 2021.

F. Lucini, K. D. Krewulak, K. M. Fiest, S. M. Bagshaw, D. J. Zuege, J. Lee, and H. T. Stelfox. Natural language processing to measure the frequency and mode of communication between healthcare professionals and family members of critically ill patients. Journal of the American Medical Informatics Association, 28(3):541-548, March 2021.

A. Sharafoddini, J. A. Dubin, and J. Lee. Identifying subpopulations of septic patients: a temporal data-driven approach. Computers in Biology and Medicine. 130:104182, March 2021.

B. Kim, M. Hunt, J. Muscedere, D. M. Maslove, and J. Lee. Using consumer-grade physical activity trackers to measure frailty transitions in older critical care survivors: exploratory observational study. JMIR Aging, 4(1):e19859, February 2021.

S. Lee, C. Doktorchik, E. A. Martin, A. D'Souza, C. Eastwood, A. Shaheen, C. Naugler, J. Lee, and H. Quan. Electronic medical record–based case phenotyping for the Charlson conditions: scoping review. JMIR Medical Informatics, 9(2):e23934, February 2021.

A. Kline, T. Kline, and J. Lee. Item response theory as a feature selection and interpretation tool in the context of machine learning. Medical & Biological Engineering & Computing, 59:471-482, February 2021.

M. Al-Jefri, R. Evans, J. Lee, and P. Ghezzi. Automatic identification of information quality metrics in health news stories. Frontiers in Public Health, 8:953, December 2020.

A. Kline, T. Kline, Z. Shakeri Hossein Abad, and J. Lee. Using item response theory for explainable machine learning in predicting mortality in the intensive care unit: case-based approach. Journal of Medical Internet Research, 22(9):e20268, September 2020.

M. Sultana, M. Al-Jefri, and J. Lee. Using machine learning and smartphone and smartwatch data to detect emotional states and transitions: an exploratory study. JMIR mHealth and uHealth, 8(9):e17818, September 2020.

B. Kim, S. McKay, and J. Lee. Consumer-grade wearable device for predicting frailty in Canadian home care service clients: prospective observational proof-of-concept study. Journal of Medical Internet Research, 22(9):e19732, September 2020.

J. Lee. Is artificial intelligence better than human clinicians in predicting patient outcomes? Journal of Medical Internet Research, 22(8):e19918, August 2020.

D. L. Olstad and J. Lee. Leveraging artificial intelligence to monitor unhealthy food and brand marketing to children on digital media. The Lancet Child & Adolescent Health, 4(6):418-420, June 2020.

J. Danziger, J. Lee, R. G. Mark, L. A. Celi, and K. J. Mukamal.  Do hyponatremia or its underlying mechanisms associate with mortality risk in observational data? Critical Care Explorations, 2(1):e0074, January 2020.

Y. Yang, J. P. Hirdes, J. A. Dubin, and J. Lee. Fall risk classification in community-dwelling older adults using a smart wrist-worn device and the resident assessment instrument-home care: prospective observational study. JMIR Aging, 2(1):e12153, June 2019.

S. T. Leatherdale and J. Lee. Artificial intelligence (AI) and cancer prevention: the potential application of AI in cancer control programming needs to be explored in population laboratories such as COMPASS. Cancer Causes & Control, 1-5, May 2019. 

L. Fuchs, M. Feng, V. Novack, J. Lee, J. Taylor, D. Scott, M. Howell, L. Celi, and D. Talmor.  The effect of ARDS on survival:  do patients die from ARDS or with ARDS? Journal of Intensive Care Medicine, 34(5):374-382, May 2019.

A. Sharafoddini, J. A. Dubin, D. M. Maslove, and J. Lee. A new insight into missing data in intensive care unit patient profiles: observational study, JMIR Medical Informatics, 7(1):e11605, January 2019.

I. E. R. Waudby-Smith, N. Tran, J. A. Dubin, and J. Lee. Sentiment in nursing notes as an indicator of out-of-hospital mortality in intensive care patients. PLoS One, 13(6):e0198687, June 2018. 

B. Y. Kim, A. Sharafoddini, N. Tran, E. Y. Wen, and J. Lee. Consumer mobile apps for potential drug-drug interaction check: systematic review and content analysis using the mobile app rating scale (MARS). JMIR mHealth and uHealth, 6(3):e74, March 2018.

D. Trtovac and J. Lee. The use of technology in identifying hospital malnutrition: a scoping review. JMIR Medical Informatics, 6(1):e4, January 2018.

A. Puri, B. Kim, O. Nguyen, P. Stolee, J. Tung, and J. Lee. User acceptance of wrist-worn activity trackers among community-dwelling older adults: mixed method study. JMIR mHealth and uHealth, 5(11):e173, November 2017.

A. Staszewska, P. Zaki, and J. Lee. Computerized decision aids for shared decision making in serious illness: systematic review. JMIR Medical Informatics, 5(4):e36, October 2017.

A. Bhattarai, A. Zarrin, and J. Lee. Applications of information and communications technologies to public health: a scoping review using the MeSH term “public health informatics". Online Journal of Public Health Informatics, 9(2):e192, September 2017.

N. N. Tran and J. Lee. Online reviews as health data: examining the association between availability of health care services and patient star ratings exemplified by the Yelp academic dataset. JMIR Public Health and Surveillance, 3(3):e43, July 2017.

B. Kim and J. Lee. Smart devices for older adults managing chronic disease: A scoping review. JMIR mHealth and uHealth, 5(5):e69, May 2017.

A. Sharafoddini, J. A. Dubin, and J. Lee. Patient similarity in prediction models based on health data: a scoping review. JMIR Medical Informatics, 5(1):e7, March 2017.

J. Lee. Patient-specific predictive modeling using random forests: an observational study for the critically ill. JMIR Medical Informatics, 5(1):e3, January 2017.

J. Lee and D. M. Maslove. Customization of a severity of illness score using local electronic medical record data. Journal of Intensive Care Medicine, 32(1):38-47, January 2017.

D. M. Maslove, J. A. Dubin, A. Shrivats, and J. Lee. Errors, omissions, and outliers in hourly vital signs measurements in intensive care. Critical Care Medicine, 44(11):e1021-e1030, November 2016.

R. Ling and J. Lee. Disease monitoring and health campaign evaluation using Google search activities for HIV and AIDS, stroke, colorectal cancer, and marijuana use in Canada: a retrospective observational study. JMIR Public Health and Surveillance, 2(2):e156, October 2016.

J. Lee, E. Ribey, and J. R. Wallace. A web-based data visualization tool for the MIMIC-II database. BMC Medical Informatics and Decision Making, 16:15, February 2016.

M. G. Shrime, B. S. Ferket, D. J. Scott, J. Lee, D. Bradford, T. Pollard, Y. M. Arabi, H. M. Al-Dorzi, R. M. Baron, M. G. Myriam Hunink, L. A. Celi, and P. S. Lai. How long is long enough? Time-limited trials for critically-ill patients with cancer. JAMA Oncology, 2(1):76-83, January 2016.

J. Lee and D. M. Maslove. Using information theory to identify redundancy in common laboratory tests. BMC Medical Informatics and Decision Making, 15:59, July 2015.

J. Lee, D. M. Maslove, and J. A. Dubin. Personalized mortality prediction driven by electronic medical data and a patient similarity metric. PLoS One, 10(5):e0127428, May 2015.

S. Nemati, B. A. Edwards, J. Lee, B. Pittman-Polletta, J. P. Butler, and A. Malhotra. Respiration and heart rate complexity: effects of age and gender assessed by band-limited transfer entropy. Respiratory Physiology & Neurobiology, 189(1):27-33, October 2013.

T. Mandelbaum, J. Lee, D. J. Scott, R. G. Mark, A. Malhotra, M. D. Howell, and D. Talmor. Empirical relationships among oliguria, creatinine, mortality, and renal replacement therapy in the critically ill. Intensive Care Medicine, 39(3):414-419, March 2013.

D. J. Scott, J. Lee, I. Silva, S. Park, G. B. Moody, L. A. Celi, and R. G. Mark. Accessing the public MIMIC-II intensive care relational database for clinical research. BMC Medical Informatics and Decision Making, 13:9, January 2013.

L. A. Celi, S. Galvin, G. Davidzon, J. Lee, D. Scott, and R. Mark. A database-driven decision support system: customized mortality prediction. Journal of Personalized Medicine, 2(4):138-148, September 2012.

I. Silva, J. Lee, and R. G. Mark. Signal quality estimation with multichannel adaptive filtering in intensive care settings. IEEE Transactions on Biomedical Engineering, 59(9):2476-2485, September 2012.

J. Lee, R. Kothari, J. A. Ladapo, D. J. Scott, and L. A. Celi. Interrogating a clinical database to study treatment of hypotension in the critically ill. BMJ Open, 2(3):e000916, June 2012.

S. Hunziker, L. Celi, J. Lee, and M. D. Howell. Red cell distribution width improves the SAPS score for risk prediction in unselected critically ill patients. Critical Care, 16(3):R89, May 2012.

J. Lee, S. Nemati, I. Silva, B. A. Edwards, J. P. Butler, and A. Malhotra. Transfer entropy estimation and directional coupling change detection in biomedical time series. BioMedical Engineering OnLine, 11:19, April 2012.

J. Lee and R. G. Mark. An investigation of patterns in hemodynamic data indicative of impending hypotension in intensive care. BioMedical Engineering OnLine, 9:62, October 2010.

D. Labib, A. Satriano, S. Dykstra, Y. Mikami, E. Prosia, P. Feuchter, J. A. Flewitt, S. Rivest, R. Sandonato, A. G. Howarth, C. Lydell, R.  Miller, L. R. Kolman, I. Paterson, G. Oudit, E. Pituskin, W. Cheung, J. Lee, and J. A. White. Baseline left ventricular contractile state is the strongest determinant of future drops in ejection fraction from cardiotoxic chemotherapy: a machine learning based CMR study. Journal of the American College of Cardiology, 79(9, Supplement):1943, 2022.

L. Lei, S. Dykstra, Y. Mikami, A. Cornhill, A. Satriano, D. S. Chew, J. A. Flewitt, S. Rivest, R. Sandonato, M. Seib, C. Lydell, A. G. Howarth, H. Quan, N. M. Fine, J. Lee, and J. White. Machine learning based prediction of cardiac-related hospitalization costs at time of diagnostic imaging: demonstration of value from multi-domain phenotypic data at time of cardiovascular MRI. Journal of the  American College of Cardiology, 79(9, Supplement):1297, 2022.

D. Labib, S. Dykstra, A. Satriano, Y. Mikami, E. Prosia, J. Flewitt, A. G. Howarth, C. P. Lydell, L. Kolman, D. I. Paterson, G. Y. Oudit, E. Pituskin, W. Y. Cheung, J. Lee, and J. A. White. Prevalence and predictors of right ventricular dysfunction in cancer patients treated with cardiotoxic chemotherapy - a prospective cardiovascular magnetic resonance study. European Heart Journal, 42(Supplement1): ehab724.2878, 2021.

Z. Shakeri Hossein Abad and J. Lee. Detecting uncertainty of mortality prediction using confident learning. The 2021 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1719-1722, 2021.

M. Al-Jefri, J. Lee, and M. James. Predicting acute kidney injury after surgery. The 2020 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5606-5609, 2020.

A. Kline, T. Kline, Z. Shakeri Hossein Abad, and J. Lee. Novel feature selection for artificial intelligence using item response theory for mortality prediction. The 2020 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5729-5732, 2020.

F. Lucini, K. Fiest, H. T. Stelfox, and J. Lee. Delirium prediction in the intensive care unit: a temporal approach. The 2020 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5527-5530, 2020.

Z. Shakeri Hossein Abad, A. Kline, and J. Lee. Evaluation of machine learning-based patient outcome prediction using patient-specific difficulty and discrimination indices. The 2020 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5446-5449, 2020.

D. Labib, A. Satriano, S. Dykstra, Y. Mikami, Z. Slavikova, P. Feuchter, S. Rivest, R. Sandonato, J. Flewitt, A. G. Howarth, B. Heydari, C. Lydell, B. Clarke, L. Kolman, E. Pituskin, W. Cheung, J. Lee, and J. A. White. Chamber volumes and deformation measures are abnormal in chemotherapy-naive cancer patients: potential implications for surveillance and definitions of cardiotoxicity. Circulation, 142(Suppl 3):A15877, 2020.

D. Labib, S. Dykstra, Z. Slavikova, P. Feuchter, S. Rivest, J. Flewitt, A. Howarth, B. Heydari, C. Lydell, B. Clarke, L. Kolman, E. Pituskin, W. Cheung, J. Lee, and J. A. White. Value of baseline clinical and CMR characteristics for the prediction of cancer therapeutics-related cardiac dysfunction: results from the Cardiotoxicity Prevention Research Initiative (CAPRI). European Heart Journal, 41(Supplement 2):ehaa946.3290, 2020.

L. Lei, S. Dykstra, A. Cornhill, D. Labib, Y. Mikami, A. Satriano, J. Flewitt, P. Feutcher, A. Howarth, B. Heydari, N. Merchant, C. Lydell, J. Lee, H. Quan, J. A. White. Development and validation of a risk model for the prediction of cardiovascular hospital admission using CMR-based phenotype in patients with known or suspected cardiovascular disease. European Heart Journal, 41(Supplement 2):ehaa946.2917, 2020.

A. K. Cornhill, S. Dykstra, Y. Mikami, J. Flewitt, M. Seib, K. Yee, P. D. Faris, C. Lydell, A. Howarth, B. Heydari, J. Lee, and J. White. Multivariable risk score based prediction of heart failure admission or death in patients with ischemic cardiomyopathy using CMR-based markers. The 23rd Annual Society for Cardiovascular Magnetic Resonance Scientific Sessions, 121-123, 2020.

A. K. Cornhill, S. Dykstra, Y. Mikami, J. Flewitt, M. Seib, K. Yee, P. D. Faris, C. Lydell, A. Howarth, B. Heydari, J. Lee, and J. White. Prediction of heart failure admission or death using a novel CMR-based risk score in patients with dilated cardiomyopathy. The 23rd Annual Society for Cardiovascular Magnetic Resonance Scientific Sessions, 269-271, 2020.

D. Labib, S. Dykstra, Z. Slavikova, Y. Mikami, K. Yee, J. Flewitt, M. Seib, S. Rivest, R. Sandonato, A. Satriano, B. Heydari, A. Howarth, C. Lydell, P. D. Faris, E. Pituskin, W. Y. Cheung, J. Lee, and J. White. Chamber volumes, mass and ejection fraction in cancer patients immediately prior to chemotherapy administration: is baseline really normal in this referral population? The 23rd Annual Society for Cardiovascular Magnetic Resonance Scientific Sessions, 858-860, 2020.

D. Labib, S. Dykstra, Z. Slavikova, Y. Mikami, K. Yee, J. Flewitt, M. Seib, S. Rivest, R. Sandonato, A. Satriano, B. Heydari, A. Howarth, C. Lydell, P. D. Faris, E. Pituskin, W. Y. Cheung, J. Lee, and J. White. Influence of modality-based threshold criteria on the diagnosis of cancer therapeutics-related cardiac dysfunction (CTRCD): what is the correct threshold for CMR? The 23rd Annual Society for Cardiovascular Magnetic Resonance Scientific Sessions, 1486-1488, 2020.

A. K. Cornhill, S. Dykstra, Y. Mikami, J. Flewitt, M. Seib, P. Faris, M. James, C. Lydell, A. Howarth, B. Heydari, N. Fine, D. V. Exner, J.  Lee, and J. White. Cardiovascular magnetic resonance imaging-based multivariable risk score for the prediction of heart failure admission or death. Circulation, 140(Suppl1):A15023, 2019.

A. Sharafoddini, J. A. Dubin, and J. Lee. Finding similar patient subpopulations in the ICU using laboratory test ordering patterns. The 2018 7th International Conference on Bioinformatics and Biomedical Science (ICBBS), 72-77, 2018.

M. A. H. Zahid and J. Lee. Mortality prediction with self-normalizing neural networks in intensive care unit patients. The 2018 IEEE-EMBS International Conference on Biomedical and Health Informatics, 226-229, 2018.

N. Tran and J. Lee. Using multiple sentiment dimensions of nursing notes to predict mortality in the intensive care unit. The 2018 IEEE-EMBS International Conference on Biomedical and Health Informatics, 283-286, 2018.

J. Lee. Personalized mortality prediction for the critically ill using a patient similarity metric and bagging. The 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics, 332-335, 2016.

Z. Zhang, J. Lee, D. J. Scott, L. Lehman, and R. G. Mark. A research infrastructure for real-time evaluation of predictive algorithms for intensive care units. The 2013 ICME International Conference on Complex Medical Engineering, 109-114, 2013.

L. Lehman, M. Saeed, W. Long, J. Lee, and R. Mark. Risk stratification of ICU patients using topic models inferred from unstructured progress notes. The 2012 American Medical Informatics Association Annual Symposium, 505-511, 2012.

J. Lee, D. J. Scott, M. Villarroel, G. D. Clifford, M. Saeed, and R. G. Mark. Open-access MIMIC-II database for intensive care research. The 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 8315-8318, 2011.

I. Silva, J. Lee, and R. Mark. Photoplethysmograph quality estimation through multichannel filtering. The 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 4361-4364, 2011.

J. Lee and R. G. Mark. A hypotensive episode predictor for intensive care based on heart rate and blood pressure time series. Computing in Cardiology, 37:81-84, 2010.

J. Lee, J. A. Dubin, and D. M. Maslove. Mortality prediction in the ICU. Secondary Analysis of Electronic Health Records, MIT Critical Data (editor), Chapter 21, pp. 315-324. Springer Open. ISBN 978-3-319-43742-2. September 2016.

M. Nikjoo, A. Kushki, J. Lee, C. Steele, and T. Chau. Reputation-based neural network combinations. Artificial Neural Networks - Methodological Advances and Biomedical Applications, K. Suzuki (editor), Chapter 8, pp. 151-170. InTech Publishing. ISBN 978-953-307-243-2. April 2011.

A. Kline and J. Lee. Machine learning capability: a standardized metric using case difficulty with applications to individualized deployment of supervised machine learning, arXiv:2302.04386, February 2023.

Data for Healthy Aging (D4HA) Working Group. Mobile technology and data-informed approaches for healthy aging and aging-in-place, [Position Paper], October 2020.

The Royal College of Physicians and Surgeons of Canada Council Task Force on Artificial Intelligence and Emerging Digital Technologies.  Task force report on artificial intelligence and emerging digital technologies, [Report], April 2020.

R. Rebutoc and J. Lee. Innovative technologies for pan-Canadian surveillance of climate change, [Report], 2019.

Y. Xu, J. Lee, and  J. A. Dubin. Similarity-based random survival forest, arXiv preprint arXiv:1903.01029, March 2019. 

B. Kim and J. Lee. Mobile & sensor technology, big data and artificial intelligence for healthy aging, [White Paper], 2019.