| Summary: | 碩士 === 國立高雄科技大學 === 電機工程系 === 107 === Based on the previous research, this thesis is based on the perspective of preventive medical treatment, and developed the "Intelligent Valvular Heart Disease Diagnosis Auxiliary System ". This system predicts the occurrence of valvular heart disease early through AI, ToT and cloud technology. And through the experimental design method to adjust the parameters in the system.
The system is divided into "four main processes, and three subsystems". First collect heart sound signals through the evaluation board and send them to the cloud server. In the server, data preprocessing and convolutional neural networks for feature extraction and modeling. In the process, the "experimental design" and "modeling analysis" are used to optimize the model parameters and analyze the model. After the signal is sent to the server, the analysis is performed through the pre-trained model and can be completed in ten seconds. Finally, the user can log in to the server through the application to view the analysis result, and can initially determine whether the heart valve function is abnormal.
It is hoped that through such a convenient and timely monitoring system, the people can help the first time to find the initial symptoms of heart disease. And with the combination of cloud technology, medical caregivers can provide the necessary consultation or assistance at the first time to provide the demand for smart medical care market development trends.
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