Special series: Artificial intelligence application for urologic cancer detection and classification

Artificial Intelligence (AI) has revolutionised urologic cancer detection by leveraging principles from computer science, machine learning and deep learning. In this context, AI serves as a powerful tool to improve the accuracy and efficiency of cancer diagnosis and treatment.

Assoc. Prof. Cacciamani shares his knowledge how computer science forms the foundation of AI algorithms, enabling the processing and analysis of vast datasets, including medical images and patient records. Machine learning techniques, a subset of AI, are applied to these datasets to create predictive models that can identify patterns and anomalies within patient data. Deep learning, a specialised branch of machine learning, excels in image recognition tasks and has been instrumental in the interpretation of medical images like CT scans, MRI scans, and histopathological slides.

By implementing AI in urologic cancer detection, healthcare professionals can achieve faster and more accurate diagnosis, early cancer detection, and personalised treatment recommendations. AI systems can assist in the identification of tumours, tracking their growth over time, and predicting patient outcomes. This integration of AI technologies enhances the quality of patient care, potentially leading to better survival rates and improved overall well-being for individuals with urologic cancers.

This podcast was produced in collaboration with the YAU Urotechnology group. For more EAU podcasts, please go to your favourite podcast app and subscribe to our podcast channel for regular updates: Apple Podcasts, Spotify, Google Podcasts.