Less Clicks, More Care: Helping Radiologists Rediscover Their Craft
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About
Radiology is at a tipping point. With surging imaging volumes, outdated workflows, and mounting pressure on radiologists, reporting inefficiencies remain a critical bottleneck in delivering timely, accurate care. But what if generative AI could change everything?
Join us for an engaging webinar featuring a fireside chat between Dr. Franz Pfister and Dr. Avez Rizvi as they explore the current challenges in radiology reporting and how AI is redefining the reporting process, alleviating tedious tasks, and unlocking new efficiencies in radiology.
Discover how cloud-native and generative AI-powered solutions can finally deliver on the promise of streamlined, standardized, and scalable radiology reporting—empowering radiologists to focus on what they do best: interpreting images and improving patient outcomes.
Don’t miss this opportunity to hear from industry leaders shaping the future of radiology. Plus, bring your questions for an interactive Q&A session to close out the event!
Agenda
Breaking the Bottleneck: Addressing the Biggest Challenges in Radiology Reporting
Radiologists today are burdened with surging imaging volumes, outdated workflows, and rising burnout. Reporting inefficiencies slow down diagnosis and impact patient outcomes and radiologist well-being. In this session, we’ll examine the key pain points in modern radiology workflows and discuss the urgent need for generative AI-driven efficiency in reporting.
AI-Powered Efficiency: How Generative AI is Reducing Clicks and Enhancing Accuracy
With the increasing demands on radiologists, generative AI offers a powerful solution—automating repetitive tasks, standardizing reports, and improving diagnostic accuracy. This session will explore how generative AI enhances efficiency while keeping radiologists in full control, allowing them to spend more time interpreting images and less on administrative work.
Scaling AI Adoption: The Role of Cloud-Native Solutions in Radiology
As AI integration expands, scalability and interoperability become critical. Cloud-native AI solutions ensure seamless workflow integration, data security, and standardization across healthcare institutions. Learn how leading hospitals are adopting cloud-based AI to improve collaboration, optimize reporting workflows, and drive long-term advancements in radiology.
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Speakers
Avez Rizvi, MD, is the physician CEO and founder of RADPAIR, a leading AI-powered platform that automates and enhances radiology reporting. A U.S. board-certified radiologist, Dr. Avez holds a Bachelor's degree in Biomedical Engineering from Columbia University, a Master’s in Applied Physiology, and a Doctorate in Medicine from The Chicago Medical School. With 12 years of experience in various startup roles and over a decade of expertise in AI, Dr. Avez launched RADPAIR to address critical inefficiencies in radiology workflows. RADPAIR uses generative AI to automate report generation, improve accuracy, and boost productivity.
Dr. Franz MJ Pfister is a medical doctor, data scientist, and entrepreneur, recognized as a leading expert at the intersection of AI, data, digitization, and healthcare. He studied medicine at Ludwig Maximilian University of Munich and Harvard Medical School, earning a medical doctorate in neuroscience. He also holds an MBA from Munich Business School and a Master’s in Data Science from LMU Munich. As CEO and co-founder of deepc, a Munich-based AI platform company, Franz focuses on advancing Radiology AI to improve patient care, optimize clinical processes, and enable personalized medicine.
