Accelerating Health Care Inference Using DL Boost

摘要

Need of healthcare resources for the emergency patients are huge and it is not met by the current healthcare technology, in most developing countries. Drawing inference for a healthcare model with their corresponding weights to the various parameters would bring many strategies to infer with the output of Model for the given input. This Inference Models have taken the weighted average of outputs of all the models. And by Using Artificial Intelligence with Machine Learning and Clinical expertise in the domain of Healthcare outperforms the existing Healthcare Systems. Intent extraction is done using various parameters and that enhances the assistive intelligence. The results are passed to the subsequent stages and that would help and improve the inference mechanisms. The clinical process guidelines in the corpus may be considered as one of the inputs and various healthcare parameters can be feature scaled and the resultant architecture provides a positive impact in healthcare systems decision making.