Abstract

Of late, long short-term memory (LSTM) has proven its worth in medical diagnosis. Hence, there is a need to explore this special version of recurrent neural network (RNN), which can learn long-term dependencies. LSTM addresses the short-term memory problem of basic RNNs. In this paper, an in-depth study of LSTM is done with the help of a few real-life examples. Some of the recent advances of LSTM in COVID-19 and other lung disease diagnoses have also been discussed.

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