Can machine learning complement traditional medical device surveillance? A case study of dual-chamber implantable cardioverter–defibrillators

MLA

Ross, Joseph S., et al. Can Machine Learning Complement Traditional Medical Device Surveillance? A Case Study of Dual-Chamber Implantable Cardioverter–defibrillators. Jan. 2017. EBSCOhost, https://doi.org/10.2147/MDER.S138158.

APA

Ross, J. S., Bates, J., Parzynski, C. S., Akar, J. G., Curtis, J. P., Desai, N. R., Freeman, J. V., Gamble, G. M., Kuntz, R., Li, S.-X., Marinac-Dabic, D., Masoudi, F. A., Normand, S.-L. T., Ranasinghe, I., Shaw, R. E., & Krumholz, H. M. (2017). Can machine learning complement traditional medical device surveillance? A case study of dual-chamber implantable cardioverter–defibrillators. https://doi.org/10.2147/MDER.S138158

Chicago

Ross, Joseph S, Jonathan Bates, Craig S Parzynski, Joseph G Akar, Jeptha P Curtis, Nihar R Desai, James V Freeman, et al. 2017. “Can Machine Learning Complement Traditional Medical Device Surveillance? A Case Study of Dual-Chamber Implantable Cardioverter–defibrillators,” January. doi:10.2147/MDER.S138158.