Medical Diagnosis using Verbal Description to Classify the Category of the Ailment
International Journal for Research in Applied Science and Engineering Technology
A huge amount of unstructured text data that contains valuable information over the online. This text is more volatile and changing rapidly making hard to process, read, extract and process. Natural language Processing (NLP) may be a subfield of linguistics which is worried with interactions with text data accustomed extract the key information. NLP helps to beat the challenges which is related to text data vulnerability. There are numerous publicly available unstructured text data. Among those
... t data. Among those we chose medical text data which is comprised of description of patients within the text and voice format. Basically, doctors follow an explicit procedure of collecting data of assorted symptoms or anomalies that a patient experiences so as to research true and treat the condition. Often the patient has vague memory of what and when these anomalies have occurred. we aim to form accurate records of those ailments together with when it occurred to assist doctors better understand the circumstance in as little time as possible. We used different machine and deep learning model to extract the summary from the statement text data to classify the ailments.