While AI has been a key theme at the Radiological Society of North America (RSNA) conference for several years, this year marked a pivotal shift: foundation models emerged as the transformative force poised to redefine healthcare workflows, diagnostics and patient care.
As Elad Walach, CEO of Aidoc, observed, the conversation at RSNA has evolved significantly over the past three years. Previous discussions centered around the potential of AI in healthcare; by last year, scalability and enterprise platforms took the spotlight. In 2024, foundation models emerged as the next phase of clinical AI.
These models, trained on vast datasets and designed for generalizability, promise to tackle the most pressing challenges in healthcare AI, including accuracy, integration and real-world validation. Aidoc’s announcement of CARE1™, our first clinical-grade foundation model, exemplifies this shift.
The message was clear: the future of clinical AI isn’t about theoretical potential or flashy demos, but in delivering measurable, real-world impact.
At the RSNA plenary session, Nina Kottler, MD, MS, FSIIM, Associate Chief Medical Officer for Clinical AI at Radiology Partners, delivered a powerful message: radiologists must lead the charge in AI adoption.
Acknowledging concerns within the profession, she noted that radiology, a field steeped in tradition, is understandably cautious about change. However, she urged radiologists to take a proactive role in shaping AI adoption, citing the famous quote: “The best way to predict the future is to create it yourself.”
Dr. Kottler urged radiologists to drive AI innovation, ensuring these tools align with clinical needs, patient safety and professional standards. Her message resonated with the conference’s overarching theme: collaboration and leadership are essential to unlocking AI’s transformative potential.
RSNA 2024 also reflected a broader shift in mindset: organizations are no longer just experimenting with AI – they’re serious about implementing it.
As Eric Topol, MD, founder and director of the Scripps Research Translational Institute, noted, the progress toward multimodal and unsupervised learning models is driving the industry closer to a future of precision medicine. The concept of “digital twins,” virtual patient replicas that simulate clinical scenarios, offers a glimpse into what’s possible when foundation models are fully realized.
However, enthusiasm was tempered by recognition of the challenges ahead. Regulatory frameworks must adapt to accommodate multimodal AI devices, and trust issues among radiologists, including concerns about liability, require education and transparency to overcome.
Radiology is at a transformative juncture. Foundation models are no longer just a buzzword – they represent the next frontier of clinical AI.
As Walach said, success depends on moving beyond the hype to deliver real-world impact. By focusing on accuracy, integration and validation, the industry can ensure that these innovations translate into life-saving solutions for patients.
RSNA 2024 underscored the power of collaboration between clinicians, AI developers and regulators. The future of radiology lies in a synergistic relationship between humans and machines, enhancing care delivery, addressing pressing challenges and unlocking new opportunities for innovation.
Missed the chance to connect with us at RSNA 2024? Request a meeting with one of our AI specialists to discuss your organization’s unique challenges and opportunities.
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