Jawed Ahmed, M. A. Alam, Abdul Mobin, Shahla Tarannum
{"title":"肥胖评估的软计算方法","authors":"Jawed Ahmed, M. A. Alam, Abdul Mobin, Shahla Tarannum","doi":"10.1109/ICRITO.2016.7784946","DOIUrl":null,"url":null,"abstract":"Body Mass Index is treated as an indicator to the case of pre-obesity and obesity. BMI values for pre-obesity and obesity are different. The range of BMI for pre-obesity is 25.00-29.99 while for obesity it is 30.00 or above. There is just a mere difference of 0.01 between 29.99 and 30.00. This little difference may be due to either wrong measurement in BMI or wrong diagnosis by doctor. But this difference may affect the health status of patient by changing the category from pre-obese to obese or obese to pre-obese. With the help of soft computing techniques, the wrong measurement in BMI or wrong diagnosis by medical practitioners may be either removed or minimized. In this paper we have used intuitionistic fuzzy logic, a kind of soft computing technique.","PeriodicalId":377611,"journal":{"name":"2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A soft computing approach for obesity assessment\",\"authors\":\"Jawed Ahmed, M. A. Alam, Abdul Mobin, Shahla Tarannum\",\"doi\":\"10.1109/ICRITO.2016.7784946\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Body Mass Index is treated as an indicator to the case of pre-obesity and obesity. BMI values for pre-obesity and obesity are different. The range of BMI for pre-obesity is 25.00-29.99 while for obesity it is 30.00 or above. There is just a mere difference of 0.01 between 29.99 and 30.00. This little difference may be due to either wrong measurement in BMI or wrong diagnosis by doctor. But this difference may affect the health status of patient by changing the category from pre-obese to obese or obese to pre-obese. With the help of soft computing techniques, the wrong measurement in BMI or wrong diagnosis by medical practitioners may be either removed or minimized. In this paper we have used intuitionistic fuzzy logic, a kind of soft computing technique.\",\"PeriodicalId\":377611,\"journal\":{\"name\":\"2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRITO.2016.7784946\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRITO.2016.7784946","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Body Mass Index is treated as an indicator to the case of pre-obesity and obesity. BMI values for pre-obesity and obesity are different. The range of BMI for pre-obesity is 25.00-29.99 while for obesity it is 30.00 or above. There is just a mere difference of 0.01 between 29.99 and 30.00. This little difference may be due to either wrong measurement in BMI or wrong diagnosis by doctor. But this difference may affect the health status of patient by changing the category from pre-obese to obese or obese to pre-obese. With the help of soft computing techniques, the wrong measurement in BMI or wrong diagnosis by medical practitioners may be either removed or minimized. In this paper we have used intuitionistic fuzzy logic, a kind of soft computing technique.