Analysis Of Diagnostic Value of cervical Cancer Disease Through Artificial Intelligence Based System
Article No.: 127, Pages 1 - 3
Abstract
Artificial Intelligence based systems plays a major role to generate useful insights in health care domain. Machine learning based techniques are used for predicting the early stages of major illnesses, such as cancer and kidney. Finding an effective treatment for cervical cancer at right time is need in current scenario, as it is the second most common cancer in women globally. Due to the complexity and variation of the illness, it could be difficult to accurately recognize using images of cervical cancer. This study reviewed a variety of machine learning classification techniques used for prediction of cervical cancer. The Study concludes that various. Multilayer Perceptron (MLP), Random Forest, K-Nearest Neighbor, Decision Tree, Logistic Regression, SVM, Gradient Boosting and AdaBoost have been used to predict cervical cancer and aid in early diagnosis. Many studies have been done using University of California, Irvine (UCI) Machine Learning Repository.
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Published In
November 2023
1215 pages
ISBN:9798400709418
DOI:10.1145/3647444
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 May 2024
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ICIMMI 2023
ICIMMI 2023: International Conference on Information Management & Machine Intelligence
November 23 - 25, 2023
Jaipur, India
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