作者
Nasser Taleb, Shahid Mehmood, Muhammad Zubair, Iftikhar Naseer, Beenu Mago, Muhammad Umar Nasir
发表日期
2022/2/16
研讨会论文
2022 International Conference on Business Analytics for Technology and Security (ICBATS)
页码范围
1-6
出版商
IEEE
简介
A high mortality rate is associated with ovarian cancer, one of the most common types of cancers in women. Ovarian cancer refers to a group of disorders that develop in the ovaries and spread to the fallopian tubes and peritoneum. Treatment is most effective when ovarian cancer is discovered in its early stages. Machine learning has recently demonstrated that it is capable of better identifying ovarian cancer and its stages. Most modern research studies on ovarian cancer use a single classification model, leading to poor performance in diagnosis. For the detection of ovarian cancer, the highly sophisticated and efficient machine learning algorithms Support vector machine (SVM) and K-Nearest Neighbor (KNN) are employed in this study. Before diagnosing illness, the suggested approach can optimize and standardize data. Experimental results show that SVM has outperformed KNN in both training and validation …
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N Taleb, S Mehmood, M Zubair, I Naseer, B Mago… - 2022 International Conference on Business Analytics …, 2022