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Study on Female Patients' Mammographic Texture Features
Sponsor: Tampere University Hospital
Summary
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.
Official title: A Cohort Study on feMale Patients' mammogRaphic texturE featureS: the COMPRESS Trial
Key Details
Gender
FEMALE
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
200
Start Date
2024-06-17
Completion Date
2038-12-15
Last Updated
2024-06-21
Healthy Volunteers
No
Interventions
AI tool
Both the arms will undergo the use of "AI tool" developed in the group. The tool will be trained to detect outcomes.