Breast cancer detector software (BCDS) using case-based reasoning - Ahmad Bukhari, Abdullah (2015)
These studies are being conducted to determine the most suitable Artificial Intelligent Technique to be implement in software Breast Cancer Detector (CBR). Breast Cancer Detector problem is to compare similarity of the new case to the old case which is have more than hundred record case. This is to ensure the less take time to compare one by one over the hundred case to a new case. The objective of this project is to develope the prototype to do the comparism of a new case with existing case of the breast cancer. Case Base Reasoning (CBR) is capable of solving the measurement of similarity and less take time to find the highest similarity. CBR consist four phase to be done to solve the similarity measurement. The first phase is retrieve that is problem (new case) is retreived. The second phase is reuse that is reuse the solved case and calculate to find the suggested solution orit called the highest similarity in percentage. The third phase is revise which is process to confirm solution (teste or repaired case). The last phase is retain. The machine learn in other mean the machine save the new case if the new case does not have the highest similarity and the doctor should do the phisycal check. The calculation that used to calculate the similarity measure is called Feature-Based Similarity Measure algorithm.