Research and Implementation for Rural Medical Information Extraction Method

Currently, the input of rural clinic system in china is the symptom from patients' descriptions. However, the existing problems in patients' descriptions are irregular and colloquial description, too much irrelevant information, etc. We need to use information extraction technology to extract more useful information as the input information of the following procedure for better matching between symptom and illness and enhancing the accuracy of the clinic. We designed an information extraction method for rural clinic using open source tools. Based on the machine learning methods, we extract time and degree information was extracted from the patients' descriptions. We designed and implement parallelization of the algorithms to speed up the response.