Fuzzy Based Treatment Model for Critical Healthcare System

• Published in: 2021 2nd International Conference on Intelligent Engineering and Management (ICIEM) pp. 193 - 198
• Main Authors: Akila, D., Balaganesh, D.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.04.2021
• Subjects: Brain modeling; critical diseases; Diseases prediction; Fuzzy inference system; Fuzzy logic; Health care system; Knowledge base; Knowledge based systems; Medical services; Ontologies; Predictive models; Stroke (medical condition); Treatment
• DOI: 10.1109/ICIEM51511.2021.9445335

An intelligent system is needed to envisage dangerous diseases and offer the doctors to decide and take action on such patients. Most of the existing healthcare systems concentrate on very few diseases and result in incorrect predictions. This paper proposes a Fuzzy based treatment model (FBTM) for the essential healthcare system. It provides early detection and treatment of critical diseases such as Heart attack, Stroke, Cancer, Kidney failure and Brain tumor. In the first phase, based on a medical knowledge base (MKB), a medical Ontology model (MOM) is developed, which will predict the chances of a patient having an acute disease. Then, the medical information resulting from the ontology and the rules are then forwarded to the Fuzzy inference system to support giving proper treatment based on the attained knowledge. The Fuzzy based method provides an acute caution to high-risk patients. It also provides treatment strategies to patients according to their disease stage.