Master's Thesis at the University of Basrah Explores an Intelligent Diagnostic System for predicting Liver Cirrhosis
A master's thesis at the College of Computer Science and Information Technology at the University of Basrah explored an intelligent diagnostic system for predicting liver cirrhosis using data mining and machine learning techniques.
The thesis, presented by student Duaa Subaih Ali, aimed to propose and implement an effective automated system for predicting the early stages and progression of liver cirrhosis in patients based on medical records. The aim was to use machine learning algorithms and data preprocessing techniques to improve model performance, increase interpretability, and reduce execution time.
The thesis included an ensemble learning approach, combining multiple individual classifiers into a single framework to produce a more reliable and accurate predictive model. This approach combines the strengths of individual models and achieves the best possible performance in predicting the stages of liver cirrhosis.
Department of Media and Governmental Communication
