Paper—Machine Learning Based Emergency Patient Classification System Machine Learning Based Emergency Patient Classification System https://doi.org/10.3991/ijoe.v17i05.22341 Supattra Puttinaovarat, Siwipa Pruitikanee, Jinda Kongcharoen Prince of Songkla University, Surat Thani, Thailand Paramate Horkaew () Suranaree University of Technology, Nakhon Ratchasima, Thailand phorkaew@sut.ac.th Abstract—Public Health Office and the risk map created from the patient in- formation. Many provincial hospitals currently have to admit a large number of patients to their emergency room. Each year, the number outgrow limited medical resources, causing tremendous operational delay, and thus undermining quality of medical services. In addition, existing ER flows remain lacking means of com- municating with patients’ relatives and notifying them with treatment status of patients under their care. To addresses these concerns, registered nurses with ex- periences are required not only to make initial patient screening and prioritiza- tion, but also to serve as liaison between physicians and patients’ relatives. These double tasks impose great burden to already overloaded medical staffs. An emer- gency patient classification system, based on support vector machine was devel- oped. It was implemented as a web application, written in PHP, and running on MySQL database. GIS technology was employed to analyze spatial data and pro- ducing relevant reports. The proposed system could classify emergency patient into different groups based on their severity, according to the government stand- ard. The resultant recommendation, verified by a nurse on duty, as well as treat- ment status were presented to patients’ relatives on a digital screen. Moreover, the hospital was able to use the summarized reports, in both standard and spatial forms, for its managerial purposes. The develop system could help the hospital to make the most of their limit resources for treating emergency patients. The produced reports were useful for making relevant policies and executive plan- ning. Keywords—Emergency Patient Classification, Emergency Room, Hospital In- formation System, Spatial Analysis, Machine Learning 1 Introduction Emergency room (ER) in a hospital provides treatment and medical care to people with injuries or acute illnesses [1][2]. Typical symptoms are, for examples, stomach- ache, headache, insect bites, accidents, seizure, etc. Regularly positioned at an ER screening point in most hospitals are registered nurses [3] [4] [5]. Unfortunately, due to iJOE ‒ Vol. 17, No. 05, 2021 133