Breast Cancer Treatment

Breast cancer treatment research focuses on improving patient outcomes through more effective and personalized therapies, alongside mitigating treatment-related side effects. Current research employs diverse approaches, including deep learning models (like vision transformers and variational autoencoders) for analyzing multimodal data (imaging, genetics, clinical records) to predict survival risk and treatment response, and natural language processing to glean insights from patient-reported experiences on social media. These advancements aim to optimize treatment selection, predict potential cardiotoxicity, and even improve the aesthetic outcomes of breast cancer treatments, ultimately leading to better patient care and improved quality of life.