Eliezer Bose, PhD, AGACNP-BC
Eliezer Bose, PhD, AGACNP-BC, is an Associate Professor in the School of Nursing at MGH Institute of Health Professions.
Dr. Bose received his master’s and PhD degrees from the University of Pittsburgh and is a board-certified adult-gerontology acute care nurse practitioner. He also previously trained and worked as an engineer in India, where he learned and developed a love for computer programming which he continues to use for his research in big data. Dr. Bose’s research training at the University of Pittsburgh, in collaboration with Carnegie-Mellon University, focused on deriving cardiorespiratory instability phenotypes in a monitored patient-unit using machine learning.
Dr. Bose’s research focuses on cardiometabolic diseases, in particular, to identify what patients are at greatest risk and when patients are at greatest risk. His research program entails a combination of machine learning, and network medicine approaches integrating gut microbiota to uncover phenotypes that could help diagnose and predict the natural evolution of cardiometabolic diseases and the personalized medicine response to treatment.
PhD University of Pittsburgh
MSN Adult Gerontology Acute Care Nurse Practitioner, University of Pittsburgh
Bose, E., Maganti, S., Bowles, K., Brueshoff, B., Monsen, K. (2019). Machine learning methods for identifying critical data elements: Toward reduced nursing documentation burden. Nursing Research.68(1). DOI: 10.1097/NNR.0000000000000315
Garcia, A., Bose, E., Zuniga, J..W. Zhang (2019). Mexican Americans' Diabetes Symptom Prevalence and Clusters. Applied Nursing Research.46, 37-42. DOI: 10.1016/j.apnr.2019.02.002
Bose, E., Radhakrishnan, K. (2018). Using unsupervised machine learning to identify subgroups among home health heart failure patients using telehealth. Computers Informatics and Nursing.36(5). DOI: 10.1097/CIN.0000000000000423
Bose, E., Clermont, G., Chen, L., Dubrawski, A., Ren, D., Hoffman, L., Pinsky, M.R., Hravnak, M. (2017). Cardiorespiratory instability in monitored step-down unit patients: using cluster analysis to identify patterns of change. Journal of Clinical Monitoring and Computing. DOI: 10.1007/s10877-017-0001-7
Bose, E., Chen, L., Clermont, G., Dubrawski, A., Pinsky, M.R., Ren, D., Hoffman, L., Hravnak, M. (2017). Risk for Cardiorespiratory Instability Following Transfer to a Monitored Step-Down Unit. Respiratory Care. 62(4). DOI: 10.4187/respcare.05001