Date of Award
2021
Document Type
Thesis
Publication Status
Version of Record
Submission Date
October 2026
Thesis/Dissertation Advisor [Chair]
Muhammad, Wazir
Abstract
Liver cancer is the sixth most common type of cancer worldwide and is the third leading cause of cancer related mortality. Several types of cancer can form in the liver. Hepatocellular carcinoma (HCC) makes up 75%-85% of all primary liver cancers and it is a malignant disease with limited therapeutic options due to its aggressive progression. While the exact cause of liver cancer may not be known, habits/lifestyle may increase the risk of developing the disease. Several risk prediction models for HCC are available for individuals with hepatitis B and C virus infections who are at high risk but not for general population. To address this challenge, an artificial neural network (ANN) was developed, trained, and tested using the health data to predict liver cancer risk. Our results indicate that our ANN can be used to predict liver cancer risk with changes with lifestyle and may provide a novel approach to identify patients at higher risk and can be bene ted from early diagnosis.
Extent
38 p.
Recommended Citation
Ataei, Afrouz, "Liver Cancer Risk Quantification through an Artificial Neural Network based on Personal Health Data" (2021). Electronic Theses and Dissertations 2020 - Present. 766.
https://digitalcommons.fau.edu/etd_general/766
Identifier
FA00013742
Comments
Includes bibliography.|Thesis (PMS)--Florida Atlantic University, 2021.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.