In-depth understanding of LSTM and its recent advances in lung disease diagnosis
Department of Electronics and Communication Engineering, Girijananda Chowdhury Institute of Management and Technology-Guwahati, Assam, India.
World Journal of Advanced Research and Reviews, 2022, 14(03), 517–522
Article DOI: 10.30574/wjarr.2022.14.3.0602
Publication history:
Received on 16 May 2022; revised on 19 June 2022; accepted on 21 June 2022
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.
Keywords:
Recurrent neural network; Vanishing gradient; Long short-term memory; Deep learning; COVID-19
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