Improved Healthcare Monitoring of Cardiovascular Patients in Time-Series Fashion Using Deep Learning Model
Keywords:
Decision Support, Cardio Vascular System, Time Series Forecasting, Deep LearningAbstract
In this paper, we develop an Improved Healthcare monitoring of cardiovascular patients in time-series fashion using deep learning model. The model uses deep learning via radial basis function integrated with artificial neural network to classify the time-series data from the electrodes. When choosing the algorithm that will be used to determine the forecast, the level of accuracy that is provided by an algorithm is one of the factors that is taken into consideration. The classification is carried out in a time -series fashion and the results of which are monitored in timely fashion. The python simulation is used to design the deep learning model, where the proposed model is used to validate the time series data. The performance of the proposed model is evaluated in terms of how it compares to the performance of models that are already in use through the process of benchmarking. This approach is used in order to determine whether or not the strategy that has been presented is the one that will prove to be the successful in the long run.
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