View clinical trials related to Mammography.
Filter by:Mammography is the most common method for breast imaging, and it provides information for model building and analysis. Radiomics applied to mammography has the potential to revolutionize clinical decision-making by providing valuable insights into risk assessment and disease detection. Despite this, the influence of imaging parameters and clinical and biological factors on radiological texture features remains poorly understood. There is a pressing need to overcome the obstacle of system-inherent effects on mammographic images to facilitate the translation of radiological texture features into routine clinical practice by enabling reliable and robust AI-based or AI-aided decision-making. Furthermore, understanding the relationship between imaging parameters, textural features, and clinical and biological information supports the clinical use of AI. The objective of this study is to evaluate AI methods for clinical practice and to study how it relates to clinical factors and biological features.
In this study, it is planned to determine the effect of virtual reality applied to women before mammography on pain, anxiety and satisfaction levels. For this purpose, individuals applying for breast cancer screening will first be randomly divided into experimental and control groups. Pain, anxiety and satisfaction level evaluation forms will be applied to the experimental group before the mammography procedure. A relaxing video will be watched with virtual reality glasses and the mammography will be performed. At the end of the mammography, the relevant forms will be applied to the individuals again. The control group will not be subjected to any additional application that will continue with the applied routine.