Publication: The Clinical Decision Support System for the Snake Envenomation in Thailand
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Issued Date
2018-09-06
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2-s2.0-85057742228
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Mahidol University
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SCOPUS
Bibliographic Citation
Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018. (2018)
Suggested Citation
Apirak Hoonlor, Varodom Charoensawan, Sahaphume Srisuma The Clinical Decision Support System for the Snake Envenomation in Thailand. Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018. (2018). doi:10.1109/JCSSE.2018.8457182 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/45585
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Title
The Clinical Decision Support System for the Snake Envenomation in Thailand
Abstract
© 2018 IEEE. With the rises of the AI technology in Healthcare, researchers have been using the technology to develop a computational system to aid diagnosis, commonly known as 'Clinical Decision Support Systems (CDSSs)'. The CDSS applications currently available are usually neither free, nor optimized for treating Thai patients. In this work, we propose a new CDSS platform intended as an open platform for the CDSS application in Thailand. As a prototype and proof of concept, we developed the Mahidol Snake Envenomation Support System (MSESS), as the first C DSS a pplication u sing o ur n ew p latform. MSESS was designed to help its user formulate a treatment plan for the patient with snake bite found in Thailand, particularly in rural areas, and guide the user through the treatment flow. The treatments suggested by MSESS strictly follows the Snake Envenomation guideline provided by the Ramathibodi Poison Center. The targeted user is the medical personnel such as general practitioner seeking a medical advice from specialists. The medical personnel will first e nter t he p atient information to the CDSS. The system will then retrieve the information, submit it to the inference engine unit hosted at our central computing facilities, and display the suggested actions to the medical personnel via our application. We discuss our lesson learn from the development of MSESS for the future development of CDSS applications on our platform.