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UOT 004
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ITI əməkdaşlarının elmi işləri - tezis |
Biblioqrafik təsvir | Mamedova , M.H. Prediction of hepatocellular carcinoma using a machine learning algorithm / M.H. Mamedova , Z.G. Jabrayilova , A.A. Ahmadova , L. Garayeva // The 16th IEEE International Conference Application of Information and Communication Technologies (AICT’2022). - Washingtondc, 2022. - P. 1-4. | Annotasiya | The prevention of hepatocellular carcinoma (HCC), which is rated third for causing
death due to cancer in the world, and the selection of more effective treatment have
necessitated the development of HCC diagnosis and prediction systems using artificial
intelligence. The presented paper examines the possibility of applying machine
learning algorithms to predict liver cancer. Machine learning methods such as Logistic
Regression (LR), Support Vector Machine (SVM), Random Forest (RF) are used to
predict HCC. The HCC Dataset taken from the website Kaggle (Kaggle.com) is
referenced for the realization of prediction. This research uses the libraries scikit- learn,
Pandas, NumPy, etc. in the Jupiter programming environment to conduct experiments.
The results of the experiments are compared, and the RF classifier is estimated to
perform the highest result. Referring to this fact, the importance of using the RF
method in building an initial HCC diagnosis and prognosis system is justified. | | Elektron variant | Elektron variant |
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