Cancer Patient

Cancer patient research intensely focuses on improving diagnosis, treatment, and patient outcomes through advanced data analysis. Current efforts leverage machine learning, particularly deep learning models like transformers and recurrent neural networks, along with federated learning to address data privacy and heterogeneity across diverse datasets (including multi-omics data, medical images, and clinical notes). This research aims to enhance precision medicine by improving prediction of survival, adverse drug reactions, and treatment response, ultimately leading to more effective and personalized cancer care. The development of AI-driven tools for clinical decision support and efficient data extraction from electronic health records is a major focus, with ongoing efforts to ensure model reliability, explainability, and ethical considerations.