This paper determines the risk for cardiovascular diseases(CVDs).and nutrition level in infants aged 06 montlis using Fuzzy Cognitive Maps(FCMs).The aim of this study is to facilitates the medical experts to early det...This paper determines the risk for cardiovascular diseases(CVDs).and nutrition level in infants aged 06 montlis using Fuzzy Cognitive Maps(FCMs).The aim of this study is to facilitates the medical experts to early detects these diseases with accuracy,so that overall death ratio can be reduced.Firstly,we have introduced the concepts of FCMs and briefly refer to the applications of these methods in medical.After that,two intel ligent decision support systems for cardiovascular and malnutrition are developed using FCMs.The proposed cardiovascular risk assessment system takes six inputs:chest pain,cholesterol,heart rate,blood pressure,blood sugar,and old peak and determines CVDs risk.The second decision support system of malnutrition diagnosis takes twelve inputs:breastfeeding,daily income,maternal education,colostrum intake,energy intake,protein intake,vitamin A intake,iron intake,family size,height,weight,head circumference,and skin fold thickness and diagnoses the nutrition level in infants.We have explained the working of both decision support systems using case studies.展开更多
文摘This paper determines the risk for cardiovascular diseases(CVDs).and nutrition level in infants aged 06 montlis using Fuzzy Cognitive Maps(FCMs).The aim of this study is to facilitates the medical experts to early detects these diseases with accuracy,so that overall death ratio can be reduced.Firstly,we have introduced the concepts of FCMs and briefly refer to the applications of these methods in medical.After that,two intel ligent decision support systems for cardiovascular and malnutrition are developed using FCMs.The proposed cardiovascular risk assessment system takes six inputs:chest pain,cholesterol,heart rate,blood pressure,blood sugar,and old peak and determines CVDs risk.The second decision support system of malnutrition diagnosis takes twelve inputs:breastfeeding,daily income,maternal education,colostrum intake,energy intake,protein intake,vitamin A intake,iron intake,family size,height,weight,head circumference,and skin fold thickness and diagnoses the nutrition level in infants.We have explained the working of both decision support systems using case studies.
