
Show Notes
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.
What you'll learn:
Why communication challenges can occur throughout the breast cancer journey How health literacy and language barriers affect patient understanding The role of trust and shared decision-making in patient-centered care How AI could help make complex medical information easier to understand Why technology should support — not replace — human connection in healthcare
Resources: Connect with Isabel Nieto Alvarez Dr. Isabel Nieto Alvarez | LinkedIn
Connect with Maria Bernathova, MD Maria Bernathova | LinkedIn
Connect with Caroline Justich Caroline Justich | LinkedIn Hosted on Acast. See acast.com/privacy for more information.
More from Healthcare Perspectives
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.
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.