An application of case based reasoning to predict pregnancy rates of artificial reproductive technology

• Main Authors: Kuo-Min Chao, 趙國閔
• Other Authors: Kai-Ying Chen
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/pr8z86

碩士 === 國立臺北科技大學 === 工業工程與管理研究所 === 99 === With the era of declining birthrate, coupled with the rising average age of marriage, to accept the number of assisted reproductive technology increases every year, the success rate of artificial insemination has become a frequently discussed topic in recent years. Currently there are many medical institutions Jie help patients IVF embryo implantation, in order to maintain its accuracy, application of artificial intelligence and data mining technology to solve medical problems is a very important issue. In this study, case-based reasoning construct an artificial reproductive case-based reasoning mechanism, the case of all assessments by the old data, indicators for new cases of similarity comparison of the re-calculated with the AHP weights of individual indicators to effectively calculate a new case closest to the current state of the old cases in order to assist physicians in the usual human reproductive surgery to follow precedent, the diagnosis and treatment, encounter new situations can also accumulate new case, to establish a more complete case-base .