Intelligent Non-Invasive LVH Risk Prediction Techniques based on ECG Deep Learning
We developed intelligent non-invasive LVS risk prediction techniques based on electrocardiograms (ECGs) to automatically predict whether patients suffer from left ventricular hypertrophy (LVH). Our techniques outperform the traditional invasive method (e.g., CT/MRI) with high accuracy and a low cost. We cooperated with Taipei Veterans General Hospital and two Japanese hospitals to validate our techniques.
Enabling Wi-Fi Intelligence based on Deep Reinforcement Learning
Intelligent Quick Structural Safety Screening System based on Neural Network Entropy and Convolution Neural Network
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An Artificial Intelligence Medicine Recognition and Verification System in Hospital Dispensing Room
Development of AI assisted assessment and intervention system based on the culture contextualization for care of people with neurocognitive disoder.
Technology maturity：Prototype
Exhibiting purpose：Display of scientific results
Trading preferences：Negotiate by self
Coming soon!