Refresher Course: Genitourinary

RC 2407 - AI in genitourinary imaging

March 2, 11:30 - 12:30 CET

5 min
Chairperson's introduction
10 min
The many faces of AI in genitourinary imaging: segmentation, characterisation and prediction
  1. To explain the various applications of AI in genitourinary imaging, including segmentation, characterisation, and prediction.
  2. To present case studies and examples demonstrating the effectiveness of AI in improving diagnostic accuracy and workflow efficiency.
  3. To discuss the potential of AI in predicting disease progression and patient outcomes in genitourinary conditions.
10 min
Data integration in genitourinary imaging
  1. To discuss the importance of data integration in enhancing the capabilities of AI in genitourinary imaging.
  2. To explore the challenges and solutions in integrating diverse data sources, including clinical, imaging, and molecular data.
  3. To highlight successful examples of data integration leading to improved diagnostic and treatment outcomes.
15 min
The challenges and opportunities for radiologists using AI in genitourinary imaging
  1. To identify the main challenges radiologists face when incorporating AI into their practice.
  2. To explore AI's opportunities for radiologists, including improved diagnostic accuracy and efficiency.
  3. To discuss strategies for overcoming barriers to AI adoption in clinical practice.
10 min
A guide to selecting a commercially available AI tool for your needs
  1. To provide criteria and considerations for selecting appropriate AI tools for genitourinary imaging.
  2. To review and compare various commercially available AI tools, highlighting their strengths and weaknesses.
  3. To offer practical advice on implementing AI tools in clinical settings and measuring their impact on practice.
10 min
Panel discussion: What will the future of radiologists and AI look like?