Healthcare Perspectives

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.In this episode, host Julia Andes, Head of Lifecycle Products at Siemens Healthineers, is joined by MUDr. Diana Scheel MHBA, cardiac imaging specialist and member of the German Radiological Society; as well as Prof. PD Dr. Bernhard Scharinger, MSc, EdiR, EBCR, board-certified radiologist and running his own private practice.What you’ll learn:• Why healthcare has a significant environmental footprint and why procurement decisions matter• How refurbished imaging systems can reduce resource consumption and emissions• What motivated radiologist Prof. Dr. Scharinger decide on a refurbished CT system• Why sustainability and excellent patient care can go hand in hand• Practical ways healthcare providers can start acting more sustainablyResources:Connect with Julia AndesConnect with Prof. Dr Bernhard Scharinger Connect with Dr Diana Scheel

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. The success of this development relies strongly on intuitive and impactful user experience, or UX, design. Effective UX is integral to ensuring that patients and clinicians can use smart healthcare systems in ways that maintain safety and integrity and enhance user experience. The question is no longer whether higher levels of automation will play a role in radiology — it's how quickly, and where to begin.Today, host Iwona Markuszewska welcomes Dr. Shivakumar Swamy S, Head and Director of the Radiology Department and Clinical Director of the Department of Radiomics and Radiogenomics at HCG Cancer care in Bangalore, India; Dr. Yair Safriel, Co-Founder and Chief Medical Officer at Pharmascan and MEC Chair of Radiology at Morton Plant Hospital Association in Clearwater, Florida; and Ralf Bauer, radiologist and partner at RNS joint practice in Wiesbaden, Germany, to examine the future of automation in radiology.What you’ll learn in this episode: Rising imaging demand, an aging population, and lack of trained technologists have pushed the radiology system to its breaking pointHow higher levels of automation can ease this challenge and which types of exams may be the easiest entry point to introducing higher levels of automation in imaging operationsAutomation starts way before image acquisition and can be implemented easily as early as in the patient check-in processPatient trust and ease of use are of utmost importance for any automation in radiology is to be widely implemented Automation will make it easier for healthcare professionals to spend more time with patients and with more complex, time-intensive cases Connect with Iwona MarkuszewskaLinkedInDr. Shivakumar Swamy S LinkedInDr. Yair Safriel LinkedIn Dr. Ralf BauerLinkedIn

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.On today’s episode of Siemens Healthcare Perspectives, you’ll hear a panel conversation discussing AI’s increasing role in radiology, recorded live at the Radiological Society of North America’s 2025 meeting. Held in Chicago, the conference is the world's largest scientific and educational meeting for the radiologic sciences. For this discussion, host Katharina Schmidler is joined by Dr. John McMenamy, an Associate Professor of Radiology at the University of Colorado and Associate Radiology Chair at Denver Health; Kelly McFarland, WakeMed’s Executive Director of Imaging Services; and Dustin Allen, CT Scan Supervisor at WakeMed.Together, these industry leaders explore what intelligent imaging looks like in action as well as its potential to enhance quality, accelerate diagnosis, reduce burnout, and improve overall patient care. What you’ll learn in this episode:How AI is transforming radiology by improving workflow efficiencyAutomation allows more focus on patient careReal-time feedback between technologists and radiologists enhances image qualityAI tools can help identify subtle findings that may be overlookedTraining programs are essential for developing the next generation of technologistsCollaboration between health systems can enhance the benefits of AIThe vital role technologists play in patient careConnect with Katharina SchmidlerLinkedIn Connect with John McMenamyLinkedInConnect with Kelly McFarlandLinkedIn

Access to quality healthcare is still out of reach for millions worldwide — particularly in low- and middle-income countries and underserved rural areas. One of the biggest drivers of this gap is a shortage of trained healthcare workers, a challenge made worse by workforce migration, limited local training opportunities, and uneven distribution of resources.In this episode of Healthcare Perspectives, host Hagen Weissapfel, Director of Education and Customer Services for Global Access to Care at Siemens Healthineers, is joined by Melissa Culp, Executive Vice President of Member Engagement at the American Society of Radiologic Technologists (ASRT), and Dr. Geoff Ibbotson, surgeon and Executive Director of the Global Surgery Foundation (GSF). Together, they explore how education and training — scaled through digital innovation and local partnerships — can transform access to care for underserved communities.From stories of practicing in isolation in remote Nepal, to advancing imaging education in Malawi, to building global learning platforms like SURGHub, Melissa and Geoff share how sustainable, in-country solutions can empower healthcare professionals, break down systemic barriers, and save lives.What you’ll learn in this episode:Why education is one of the most sustainable forms of impact in global healthHow digital learning platforms like SURGHub are connecting providers in over 200 countriesThe role of local leadership and trust in building effective training programsHow public awareness campaigns can inspire the next generation of medical imaging professionalsThe life-or-death consequences of gaps in surgical technology access — and how training can close themWhy small, targeted investments can yield measurable improvements in health outcomesConnect with Hagen WeissapfelLinkedInConnect with Melissa CulpLinkedInConnect with Geoff IbbotsonLinkedIn

Is it possible for artificial intelligence to make healthcare more environmentally sustainable? In the field of radiology, AI may prove to be transformative. It has the potential to streamline processes, cut costs, and increase accuracy in imaging, diagnostics, and prevention.When we talk about sustainability, we often think of carbon emissions or climate change. But environmental sustainability means something much broader in healthcare: it’s about how we can preserve resources, whether cost, energy, human capital, and reduce waste and pollution, all while improving health outcomes for everyone, everywhere.Today, host Vibhas Deshpande, Head of Sustainability Innovation and Research, Americas at Siemens Healthineers, welcomes Dr. Kate Hanneman, cardiac radiologist at the University of Toronto; Dr. Charles Goh, Chief Medical Informatics Officer at Singapore General Hospital; and Tobias Heimann, head of the Department of Artificial Intelligence Germany at Siemens Healthineers, to explore how the rise of artificial intelligence is reshaping the conversation around sustainability in healthcare. Together, they’re helping define what “responsible AI” really means—and what steps healthcare leaders can take now to ensure that AI benefits patients, clinicians and health systems and preserves global resources.What you’ll learn in this episode:Why eliminating data redundancy and using foundational models are keys to keeping AI development sustainableAI is used to shorten imaging exams while still maintaining a high image quality, which contributes to energy savingsAI can help to arrive at correct diagnosis by improving clinical decision making and alignment to best practice to minimize waste in health systemsSustainability is more than a metric of emissions or kilowatts—it’s also about how we invest intellectual and clinical capital, such as freeing clinicians to do what humans can do best: connect, interpret, and care.Connect with Vibhas DeshpandeLinkedIn Connect with Kate HannemanLinkedInConnect with Charles GohLinkedInConnect with Tobias HeimannLinkedIn

Metabolic dysfunction-associated steatotic liver disease (MASLD), also known as fatty liver disease, is a chronic liver condition that affects nearly 1 in 3 people worldwide. It is closely linked to obesity, type 2 diabetes, and metabolic syndrome. Unchecked, it can progress to a more severe form of disease called Metabolic Dysfunction-Associated Steatohepatitis (MASH). Prognosticating the risk of disease progression in MASLD and MASH has traditionally involved liver biopsy, a process that involves removing a tissue sample with a hollow needle and then examining the sample under a microscope to diagnose and stage disease. However, biopsy has many limitations. Additionally, drug development for MASLD and MASH has proceeded slowly in part due to a reliance on liver biopsy to determine drug efficacy.Recently, increasing evidence is suggesting that non-invasive options, for example, imaging examinations along with blood tests that assess likelihood of disease progression such as the Enhanced Liver Fibrosis (ELF) Test, may effectively reduce the need for the more invasive alternative. Key experts in MASLD and MASH share their perspectives about how clinical evidence supports a shift in the way patients with MASLD and MASH could be evaluated in clinical practice and in research.Host Matt Gee, Director of Collaborations and External Engagement at Siemens Healthineers, is joined by Prof. William Rosenberg, Deputy Director of the Institute for Liver and Digestive Health at University College London as well as Dr. Veronica Miller, Director of the Forum for Collaborative Research at the University of California, Berkeley School of Public Health; Dr. Arun Sanyal, Professor of Medicine, Physiology, and Molecular Pathology in the Division of Gastroenterology at Virginia Commonwealth University; and Dr. Michelle Long, International Medical Vice President of Metabolic Dysfunction-Associated Steatohepatitis at Novo Nordisk and Associate Professor in the Section of Gastroenterology and Hepatology at Boston University.What you’ll learn in this episode:Liver biopsy creates several obstacles for patients and has limitationsDrug development faces challenges by the reliance on biopsy as a measure of treatment effectivenessNon-invasive tools may be suitable alternatives to liver biopsy both in clinical practice and in drug developmentConnect with Matt GeeLinkedIn Connect with Veronica MillerLinkedInConnect with William RosenbergLinkedInConnect with Michelle LongLinkedInConnect with Arun SanyalVCU.edu