Clinical Research Directory

The Impact of Artificial Intelligence-Assisted X-ray Interpretation on Radiologists' Diagnostic Performance

This study tests whether an artificial intelligence (AI) tool helps radiologists read X-rays more accurately. Radiologists read X-rays to find diseases such as pneumonia, bone fractures, and abdominal problems. AI is a computer program trained on many past X-rays. It may help radiologists spot diseases faster and more correctly. This study compares reading X-rays with the AI tool to reading X-rays without it. Who takes part * Ten radiologists from several hospitals. * X-ray images from about 300 to 500 past hospital visits. * No new X-rays are taken. * All names and ID numbers are removed from the images. What happens * Each radiologist reads the same set of X-rays twice. * One time, the radiologist reads without the AI tool. * The other time, the radiologist can see the AI result. * Half start with no AI and then switch to AI. The other half start with AI and then switch to no AI. * There is a four-week break between the two times. * The researchers measure how accurate each radiologist is. They also time how long each image takes. Possible benefits and risks * The radiologists may get no direct personal benefit. * The results may show whether AI can help doctors read X-rays better in the future. * This is a low-risk study. The AI tool never tells a patient a diagnosis directly. * A qualified radiologist always makes the final diagnosis. * Patient data is stored on a locked, encrypted server.

Bone Stimulator for Spondylolysis

This prospective study aims to investigate the effectiveness of bone stimulator therapy as adjunct treatment of spondylolysis in athletic populations. By evaluating its impact on pain reduction, functional improvement, osseous bony union and return-to-sport time, the investigators seek to provide valuable insights into the role of bone stimulation therapy as a potential treatment modality for this challenging condition.