Stroke Patient

Stroke research focuses on improving diagnosis, treatment, and rehabilitation outcomes for stroke patients, a leading cause of disability and death. Current research employs machine learning models, including deep learning (e.g., CNN-LSTMs, Transformers), and other algorithms (e.g., Random Forests, XGBoost) to analyze multimodal data (imaging, clinical records, physiological signals) for improved prediction of mortality, functional outcomes, and optimal treatment selection. These advancements aim to personalize stroke care, optimize resource allocation, and ultimately enhance patient recovery and quality of life. Furthermore, research is exploring innovative rehabilitation technologies, such as robotic systems and virtual reality, to improve patient engagement and motor recovery.