Online ISSN: 2515-8260

Keywords : the ticket can be automatically classified to Appropriate Category (out of 6 Categories) and Subcategories (Out of 21 Sub Categories) with good accuracy using Machine learning approach


A MODEL FOR IMPLEMENTING HEALTH CARE SERVICE TICKET CLASSIFICATION USING NLP

D. Anil Kumar; Sudheer Babu Punuri; P.S.Prema Kumar; A V S Pavan Kumar; Dr Mula Malyadri

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 2856-2866

Nowadays getting doctor appointment is very difficult task The Heath Care Services range from basic medical diagnostics to critical emergency services offering a ticketing system for all the telephonic calls received across all the departments.Calls to the provider can be for New Appointment, Cancellation, Lab Queries, Medical Refills, Insurance Related, and General Doctor Advise etc.The Tickets have the details of Summary of the call and description of the calls written by various staff members with no standard text guidelines. We investigate to see if, based on the Text in the ‘Summary’ and ‘Description’ of the call, the ticket can be automatically classified to Appropriate Category (out of 6 Categories) and Subcategories (Out of 21 Sub Categories) with good accuracy using Machine learning approach. We use the bag of words approach to solve the problem. Further we would try different data feature representation methods using Document Term Matrix ( tf, tf-idf, binary-tf,) and different Machine learning algorithms and see which performs better, and try to reason why one works better than the other