Recursive and Rolling Windows for Medical Time Series Forecasting: A Comparative Study
暂无分享,去创建一个
[1] Zucchini,et al. An Introduction to Model Selection. , 2000, Journal of mathematical psychology.
[2] Sandeep Sharma,et al. Anomaly Detection in Medical Wireless Sensor Networks using Machine Learning Algorithms , 2015 .
[3] Yaning Liu,et al. Anomaly Detection in Medical Wireless Sensor Networks , 2013, J. Comput. Sci. Eng..
[4] Schahram Dustdar,et al. Quality of Context: models and applications for context-aware systems in pervasive environments , 2014, The Knowledge Engineering Review.
[5] Syed Mahfuzul Aziz,et al. Sensor Anomaly Detection in Wireless Sensor Networks for Healthcare , 2015, Sensors.
[6] Ionut Cardei,et al. A Mobile Device Prototype Application for the Detection and Prediction of Node Faults in Wireless Sensor Networks , 2014, ArXiv.
[7] Joon Lee,et al. Accessing the public MIMIC-II intensive care relational database for clinical research , 2013, BMC Medical Informatics and Decision Making.
[8] K. Knight. Consistency of Akaike's Information Criterion for Infinite Variance Autoregressive Processes , 1989 .
[9] Duc Khuong Nguyen,et al. Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models , 2012 .
[10] Nasser L. Azad,et al. Vehicle speed prediction via a sliding-window time series analysis and an evolutionary least learning machine: A case study on San Francisco urban roads , 2015 .
[11] Borko Furht,et al. Anomaly Detection Scheme for Medical Wireless Sensor Networks , 2013, Handbook of Medical and Healthcare Technologies.
[12] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[13] Nigel H. Lovell,et al. Effect of Home Telehealth Data Quality on Decision Support System Performance , 2015, CENTERIS/ProjMAN/HCist.
[14] Borko Furht,et al. Sensor fault and patient anomaly detection and classification in medical wireless sensor networks , 2013, 2013 IEEE International Conference on Communications (ICC).
[15] Osman Hasan,et al. Formal reliability analysis of Device Interoperability Middleware (DIM) based E-health system using PRISM , 2015, 2015 17th International Conference on E-health Networking, Application & Services (HealthCom).
[16] Rance Cleaveland,et al. Formal verification of software-based medical devices considering medical guidelines , 2013, International Journal of Computer Assisted Radiology and Surgery.
[17] Borko Furht,et al. Anomaly Detection in Medical Wireless Sensor Networks using SVM and Linear Regression Models , 2014, Int. J. E Health Medical Commun..
[18] Marc A. Rosen,et al. Application of sliding window technique for prediction of wind velocity time series , 2014 .