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A Transformer-Based Diffusion Probabilistic Model for Vital Signs Forecasting
The model proposed in this technology, Transformer-based Diffusion Probabilistic Model for Sparse Time Series Forecasting (TDSTF), is a novel deep-learning algorithm that can be used for vital signs forecasting, data synthesis, simulation, and digital twins. Trained and tested on data from over 46,000 patients, the TDSTF technology merges transformer...
Published: 5/2/2024
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Inventor(s): Ao Li, Ping Chang, Huayu Li, Janet Roveda
Keywords(s):
Category(s): Technology Classifications > Software & Information Technology > Health IT, Technology Classifications > Software & Information Technology > Web & Internet
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