Integrating Generative AI and Deep Learning for Next-Generation Remote Smart Early Warning System for Sudden Cardiac Arrest
Our team developed a TCN model using publicly available ICU datasets and externally validated it by data from NTUH. The results show that TCN can predict over 90% of sudden cardiac arrest cases six hours before the cardiac arrest events, with an AUC of 0.96, outperforming NEWS, which has an AUC of 0.87 and a sensitivity of 81% six hours before cardiac arrest occurs. Furthermore, we utilized generative AI to predict vitals of the next hour based on patient past vital signs and medical records.
The verification mechanism of power generation using the Weather Research and Forecasting Model (WRF) and the Power Generation Geographic Information System in T-REC
Algorithm-Driven Design: Using new algorithm and deep learning model to control the microstructures generation of favorable mechanical behavior (Static & Dynamic) in additive manufacturing.
A Pioneer Novel Weakly-supervised Multi-instance Learning Framework for Genetic Expression Recognition and Survival Prediction in Digital Pathology Images
"1) Integrating AI recognition, IoT, and blockchain into traceable software and hardware for recycling UCO 2) Cutting-edge 3D learning platform powered by Spatial AI 3) Optimize use of existing buildings by making them transformable and adaptive to human needs at the click of a button 4) Non-contact image analysis and calculation technology to capture vital signs through dynamic face detection"
Technology maturity：Prototype
Exhibiting purpose：Display of scientific results
Trading preferences：Negotiate by self
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