Ovarian cancer diagnosis using a hybrid intelligent system with simple yet convincing rules

• Main Authors: Ng, Geok See, Wang, Di, Chai, Quek
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2018
• Subjects: Decision Support System; Ovarian Cancer Diagnosis; DRNTU::Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/89612; http://hdl.handle.net/10220/46272
• Institution: Nanyang Technological University

Ovarian cancer is the ninth most common cancer among women and ranks fifth in cancer deaths. Statistics show that the five-year survival rate is greater than 75% if diagnosis occurs before the cancer cells have spread to other organs (stage I), but it drops to 20% when the cancer cells have spread t...