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Browse 47,334 clinical trials for rheumatoid arthritis. Find studies that match your criteria and connect with research centers.
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NCT07312929
SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS. Hypothesis: Can the investigators develop and implement Machine Learning and Artificial Intelligence Algorithms into Clinical Information Systems to Optimize the Prescription, Delivery, and Performance of Acute Dialysis? Objective(s): 1. Identify variables surrounding identified Key Performance Indicators that may be used by Machine Learning and Artificial Intelligence algorithms to optimize the prescription and performance of acute dialysis. 2. Develop Machine Learning and Artificial Intelligence algorithms to help guide the prescription and delivery of acute dialysis in the development of Clinical Decision Support tools and Best Practice Advisories and create a ML/AI Augmented SMART DIALYSIS Digital Dashboard. 3. Implement and evaluate the performance of the developed Machine Learning and Artificial Intelligence algorithms on patient-centered and health economic outcomes. 4. Validate and benchmark the performance of the evaluated Machine Learning and Artificial Intelligence algorithms across multiple jurisdictions.
NCT07333495
This clinical study aims to investigate a new, non-invasive method for monitoring kidney function after transplantation. Currently, assessing the health of a transplanted kidney often relies on blood tests or invasive biopsies, which may not detect subtle early changes or account for each kidney's unique starting point. This research will use advanced, non-contrast Magnetic Resonance Imaging (MRI) scans to measure various aspects of kidney health, such as blood flow and oxygen levels. The study includes two main groups of participants: 1) kidney transplant donors and their matched recipients, and 2) transplant recipients whose donors are unavailable for study (e.g., deceased donors). For donor-recipient pairs, the goal is to create a personalized "baseline" for each transplanted kidney by scanning the donor before donation. This allows doctors to compare the kidney's function after transplant to its own unique starting point, potentially detecting problems much earlier. For recipients without donor data, the study will evaluate how well the MRI scans can track changes in kidney function over time on their own. Additionally, the study will analyze body composition (like fat and muscle distribution) and metabolic health to understand their relationship with transplant kidney function. We plan to enroll approximately 1000 participants across multiple hospitals. The ultimate goal is to develop a more accurate, individualized, and non-invasive tool for the early detection of transplant kidney problems, helping to improve long-term outcomes and quality of life for transplant patients.