Our research team is proposing a novel approach to reduce the spread of the disease by developing a mechanical filtration system to isolate and remove infected white blood cells. This innovative method leverages the fact that leukemia cells are larger than healthy ones, enabling their separation through a filtration process. While our primary goal is not to cure leukemia, we aim to mitigate the spread of cancer metastasis by reducing the population of circulating leukemia cells. By combining advanced filtration techniques and microfluidic technology, we anticipate developing a highly efficient and minimally invasive system to improve the quality of life for leukemia patients. 

Gossypiboma, the accidental retention of surgical sponges within a patient's body, remains a significant challenge in modern healthcare. Despite advancements in surgical techniques and protocols, human error and the complexity of certain procedures continue to contribute to this preventable complication. To address this issue, we are developing an innovative approach that leverages the power of technology to enhance surgical sponge tracking and reduce the risk of gossypiboma.

Coronary artery disease (CAD) is a critical health issue characterized by the narrowing or blockage of the coronary arteries, which supply blood to the heart. Atherosclerosis, the buildup of plaque within the artery walls, is the primary cause of CAD. This plaque can reduce blood flow to the heart muscle, leading to angina or, in severe cases, a heart attack.

Existing diagnostic methods for CAD often rely on qualitative assessments, which can be subjective and prone to errors. To address this limitation, our research aims to develop a more accurate and quantitative approach for diagnosing stenotic lesions in coronary arteries. By combining advanced imaging techniques, computational fluid dynamics, and artificial intelligence, we seek to revolutionize the diagnosis and treatment of CAD.

Our team is focused on revolutionizing cardiovascular disease diagnosis through the innovative application of artificial intelligence to heart sounds. By analyzing the intricate patterns and nuances encoded within cardiac auscultation, we aim to develop a non-invasive, highly accurate, and accessible diagnostic tool. Our project involves curating a comprehensive heart sound database, extracting meaningful spectral features, investigating pulse frequency patterns, and training advanced machine learning models to identify early signs of coronary artery disease. This groundbreaking research has the potential to significantly improve patient outcomes and pave the way for personalized preventive care strategies. 

Our research team is investigating the complex interactions between sickle cells and blood vessels to better understand the mechanisms underlying thrombosis in sickle cell disease (SCD). By using advanced simulation techniques, we aim to create virtual models of the circulatory system and study how sickle cells contribute to clot formation. Our research has the potential to identify new risk factors for thrombosis and inform the development of more effective prevention and treatment strategies for SCD patients. 

Our research team is focused on advancing our understanding of mitral valve function and dysfunction through the use of computational fluid dynamics simulations. By modeling the complex interactions between blood flow and the mitral valve leaflets, we aim to gain insights into the mechanisms underlying various heart conditions and explore potential treatment options. Our research has the potential to improve patient outcomes and contribute to the development of innovative medical devices and therapies. 

Our research team is investigating the phenomenon of blood hammer, a rare but potentially life-threatening condition caused by sudden, intense pressure waves within the blood vessels. We are particularly interested in understanding the role of thrombosis in triggering these pressure waves and the subsequent damage they can cause to arteries and the endothelium. By studying the mechanisms underlying blood hammer, we aim to develop more effective diagnostic and treatment strategies to prevent severe complications and improve patient outcomes. 

Our research leverages Computational Fluid Dynamics (CFD) to simulate airflow within the respiratory system for diagnostic and therapeutic purposes. This cutting-edge approach allows us to analyze airflow patterns, aiding in the study of drug delivery to ensure targeted and effective medication reaches the required regions. Additionally, our simulations provide insights into flow behavior under different pathological conditions, enhancing our understanding of respiratory diseases and supporting the development of advanced treatment strategies. 

Our research investigates the impact of rapid acceleration and deceleration on blood flow dynamics, particularly within brain arteries. High-speed accidents can generate extreme deceleration forces, significantly increasing blood pressure within the arteries. This sudden pressure surge may lead to vessel rupture and internal bleeding, posing life-threatening risks.

To better understand these critical conditions, we use advanced simulation techniques to model blood flow under extreme acceleration and deceleration scenarios. Our goal is to identify the thresholds at which arterial rupture occurs, providing valuable insights for improving safety measures, trauma response, and medical interventions in high-impact accidents.

Computational Fluid Dynamics (CFD) is a cutting-edge simulation tool that allows researchers to model and analyze the intricate fluid dynamics within the eye. By solving mathematical equations that describe fluid flow, heat transfer, and mechanical interactions, CFD provides unprecedented insights into ocular physiology and pathology.