How do you think AI is transforming Radiology ?
How can AI can pave the way for more accurate and efficient diagnostics? In medical imaging, there is a growing gap between the need for diagnostic imaging and the availability of specialist staff. At the same time, groundbreaking developments in the field of artificial intelligence continue to transform the face of the imaging field as we know it. In fact, AI is currently being used as an efficient and cost-reducing solution to a variety of industry challenges. In this episode, live recorded at ECR 2024 in Vienna, host Fabian Schoeck, Head of Global Product Management for Artificial Intelligence Products at Siemens Healthineers, is joined by Dr. Johannes Haubold, Senior Physician for Clinical AI Integration at University Hospital Essen and Isabelle Ayx, a Senior Radiologist at University Medical Center Mannheim, all based in Germany. What do you think ?
Advancing medicine with high-impact AI solutions
Big data is fueling innovation in healthcare Real-world medical data are the cornerstone of AI innovation in healthcare. We harness the power of data responsibly and ensure its integrity and privacy so we can develop groundbreaking AI solutions that transform healthcare. Sourcing from all five continents: Access to comprehensive health data is essential for advancing AI in healthcare. Siemens Healthineers meticulously gathers datasets from all five continents that encompasses a diverse range of sources, including public clinical registries, medical associations, and trusted research partners. These datasets contain a wealth of information, including clinical images, lab data, genomic data, and clinical data like patient histories. Protecting patient privacy: Siemens Healthineers adheres to stringent data privacy principles to ensure that patient information remains secure and protected. Before data is used in research projects, it undergoes a rigorous anonymization process to remove all personally identifiable information. This safeguards patient privacy while enabling valuable research advances. Enhancing data quality: AI applications are fundamentally dependent on the quality of the data they’re fed. Our experts thoroughly examine each data point, enriching it with additional information like anatomical landmarks, diagnostic indicators, and tumor characterizations. These annotations are crucial for developing accurate and reliable AI models that can transform healthcare.
