Automated Disease Inference For Community Health Care Using Graph Induced Neural Network - et. al., M.Dhanamalar, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
One of the main problems in the area of community health care is to identify the disease based on the symptoms and lack of medical vocabulary among the users. There are limited number of doctors and medical practitioners available in these forums. The lack of medical professionals requires an automated solution, but this solution must be capable of bridging the vo- cabulary gap between the users and the medical terms. Therefore a simple medical information retrieval and file sequencing might not be the solution, we need a system capable of processing natural language and convert the necessary terms to a suitable medical term thus leading to accurate disease inference. There are many excellent text mining algorithms that are available such as GRU and LSTM , these algorithms work excellently on health records and documents with accurate description of diseases. The community data is very vast and more relatable to the data which will actually be used in day to day usage of the algorithm. Graph based algorithms have been widely used fr natural language processing, with neural network’s capability or retention of good information and elimination of noise can actually be of a great use.