Artificial intelligence applications in oncology to augment data and support decisions

The application of Artificial Intelligence (AI) in the medical field, particularly in oncology is explored within this thesis. Research primarily focused on two areas: data augmentation and decision-making. Generative Adversarial Networks (GANs) were used to generate simulated clinical data to augment the dataset for training deep learning models, addressing data imbalance issues. Additionally, AI diagnostic models were developed which were capable of handling various formats of medical data to support clinical decision-making and personalized treatment. This research confirmed that AI techniques can produce high-quality medical data to enhance the classification performance of machine learning and deep learning models. Meanwhile, AI decision models can provide assistance to doctors in the field of oncology.