Show Notes
A diagnosis of cancer is one of the most devastating a person can receive—and worldwide, the number of new cancer diagnoses per year is on the rise, putting even more stress on patients, their families, care teams and health systems.
Today, Gabriel Haras, MD, president of Cancer Therapy Imaging at Varian, a Siemens Healthineers company, is exploring whether digital twin technology could help create a world without fear of cancer. He’s joined by Chloé Audigier, senior AI research scientist at Siemens Healthineers, and Christian Weißenberger, MD, head of outpatient care at the Center for Radiotherapy and Radio-oncology in Freiburg in Breisgau, Germany.
Find out how digital twins could transform the entire cancer care path – from early detection to treatment and follow-up care. You’ll also learn how a digital twin of an organ is created. And you’ll hear what digital twin technology could mean for patients, clinicians, and the future of oncology.
What You’ll Learn in This Episode: How the digital twin of an organ is created (03:40) Why early detection of cancer is so important (06:03) How digital twins could improve diagnosis (08:50) How digital twins could help find the right therapy (12:09) The role of digital twins in follow-up care (18:41)
Connect with Christian Weißenberger: LinkedIn
Connect with Chloé Audigier: LinkedIn Hosted on Acast. See acast.com/privacy for more information.
More from Healthcare Perspectives
In this episode of Healthcare Perspectives, host Isabel Nieto Alvarez, PhD, an expert for patient experience at Siemens Healthineers, is joined by Maria Bernathova, MD, breast radiologist and generative AI specialist, and Caroline Justich, breast cancer patient advocate and founder of the patient support initiative Be Accepted. Together, they discuss how better communication — and the responsible use of AI — could help patients feel more informed, involved, and supported throughout their care.
Across the globe, chronic kidney disease, diabetes, cardiovascular disease, and obesity continue to place a growing burden on healthcare systems. Many of these conditions develop silently, often remaining undetected until significant damage has already occurred.
Healthcare systems around the world are under increasing pressure to reduce their environmental footprint without compromising access to care, quality, or patient safety. One often overlooked opportunity is the refurbishment of imaging systems. By giving imaging systems a second life, healthcare providers can help preserve resources while continuing to deliver clinical performance.
Across the globe, radiology departments are grappling with a paradox: imaging volumes are climbing while the trained workforce needed to operate scanners is shrinking. Using AI-driven tools, a drive towards fully-automated radiology promises faster diagnoses, greater diagnostic accuracy, and more efficient workflows, improving both the patient and clinician experience. It is rapidly transforming the way medical imaging is performed, analyzed, and integrated into imaging workflows.
Medical imaging is already an integral part of modern healthcare, but as hospitals face growing imaging demand and staffing challenges, new solutions using artificial intelligence have become an effective way to help ease the load.