Deep Learning Technology to Uncover Human Thyroid Illness

Abstract

Deep learning techniques has illuminated the way ahead for large scale development on various sectors of human live. Medical applications were amongst those developments. Deep learning is used for mining knowledge that related to diseases so that, disease can be recognized in more effective ways. A large record of thyroid illness taken from hospital; cases are intensively investigated with aim of thyroid disorder detection. In this paper, Long Short Term Memory (LSTM) neural network is deployed for thyroid illness prediction. A 5000 cases were used to train the model and the model is calibrated using a bunch of performance metrics. The results are compared with those obtained by other tools such as Recurrent neural network (RNN) and Linear Vector Quantization (LVQ) algorithm. Accuracy of prediction in LSTM model is outperformed over the others.