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NEAR-INFRARED SPECTROSCOPY (NIR) BASED GLUCOSE PREDICTION USING DEEP LEARNING
NEAR-INFRARED SPECTROSCOPY (NIR) BASED GLUCOSE PREDICTION USING DEEP LEARNING
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机译：基于深度学习的近红外光谱（NIR）葡萄糖预测
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摘要
Provided is a recurrent neural network that predicts blood glucose level. The RNN includes a first long short-term memory (LSTM) network and a second LSTM network. The first LSTM network may include an input to receive near-infrared (NIR) radiation data and includes an output. The second LSTM network may include an input to receive the output of the first LSTM network and an output to output blood glucose level data based on the NIR radiation data input to the first LSTM network.
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