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Machine Learning to Predict In-Hospital Cardiac ...

By using the machine learning algorithms, this study developed a risk stratification model for predicting the occurrence of in-hospital cardiac arrest (IHCA) events in patients admitted from the em...

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Integration of an ICU Visualization Dashboard (i...

Multidisciplinary rounds (MDRs) are scheduled, patient-focused communication mechanisms among multidisciplinary providers in the intensive care unit (ICU). The surgical ICU team of National Cheng K...

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Embedding multimodal machine intelligence in the...

This project collaborates with the international team to collect a very large-scale Chinese emotional corpus. In terms of technology, the fairness of speech emotion recognition is also discussed to...

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Advanced Technologies for Designing Trustable AI...

This integrated research project follows the Taiwan's 2030 Science & Technology Vision and takes LOHAS community and inclusive technology as the major research direction. We aim to develop trustabl...

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YOLOv7

YOLOv7 is a new generation of real-time object detector, which provides the most advanced real-time object detection architecture from edge computing to cloud computing.

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A comprehensive evaluation of self-supervised sp...

Machines need annotations to learn, but human babies learn human languages with almost no annotations. Can machines do the same thing? To allow machines to learn human languages with only observati...

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