AN APPROACH FOR AUTO-GENERATING SOLUTION TO USER-GENERATED MEDICAL CONTENT USING DEEP LEARNING TECHNIQUES

• Main Authors: Faraz Bagwan, Leena Deshpande
• Format: Article
• Language: English
• Published: ICT Academy of Tamil Nadu 2018-04-01
• Series: ICTACT Journal on Soft Computing
• Subjects: Community Question Answering; Deep Learning; Health- Related Issue
• Online Access: http://ictactjournals.in/ArticleDetails.aspx?id=3428

One of many things humans are obsessive about is health. Presently, when faced with a health-related issue one goes to the web first, to find closure to his/her problem. The community Question Answering (cQA) forum allows people to pose their query and/or discuss it. Due to alike or unique nature of the health query it may go unanswered. Many a time the answers provided are ill-founded, leaving the user discontent. This indicates that the process is dependent on supplementary users or experts, in relation to their ability and/or the time taken to answer the question. Hence, the need to create an answer predictor which provides instant and better-quality result. We, therefore propose a novel scheme where deep learning is used to produce appropriate answer to the given health query. Both historical data i.e. cQA and general medical data are used to form a powerful Knowledge Base (KB), to assist the health predictor.