Self-attention based recurrent convolutional neural network for disease prediction using healthcare data.

Background And Objective: Nowadays computer-aided disease diagnosis from medical data through deep learning methods has become a wide area of research. Existing works of analyzing clinical text data in the medical domain, which substantiate useful information related to patients with disease in large quantity, benefits early-stage disease diagnosis. However, benefits of analysis not achieved well when the traditional rule-based and classical machine learning methods used; which are unable to handle the unstructured clinical text and only a single method is not able to handle all challenges related to the analysis of the unstructured text, Moreover, the contribution of all words in clinical text is not the same in the prediction of disease.