Stanford's Curtis Langlotz Joins Raidium to Enhance AI in Radiology

Stanford's Curtis Langlotz Joins Raidium's Strategic Advisory Board

In an exciting development for the world of radiology, Dr. Curtis Langlotz, a prominent radiologist and artificial intelligence (AI) expert at Stanford University, has joined Raidium's strategic advisory board. Raidium, an innovative company focused on AI imaging for radiology and oncology, announced this significant partnership on November 6, 2026.

Dr. Langlotz brings a wealth of experience to Raidium, holding positions as a Professor of Radiology, Medicine, and Biomedical Data Science at Stanford. His expertise lies in developing machine learning methods that enhance the accuracy and efficiency of medical image interpretation, ultimately aiding in the early detection of diseases and minimizing medical errors. In addition, he serves as a Senior Fellow at Stanford's Institute for Human-Centered Artificial Intelligence and leads the Center for Artificial Intelligence in Medicine and Imaging, which supports over 250 faculty members engaged in interdisciplinary machine learning research aimed at improving clinical care.

Raidium is poised to benefit significantly from Dr. Langlotz's input on the clinical validation and responsible development of AI-assisted radiology reporting. In his role, he emphasizes the importance of maintaining control for radiologists throughout the reporting process. As he stated, “The radiology report is how our work reaches patients and the clinicians who care for them, and AI has been transforming how reports are being written for a while.” This transformation necessitates that radiologists retain oversight and clarity in understanding how AI-generated drafts are formulated, ultimately assuring trust in these advanced technologies.

Dr. Langlotz's vision aligns with Raidium's mission to create AI tools that empower radiologists rather than replace them. He noted that establishing trust in AI-driven radiology hinges on validating the entire system, rather than simply measuring isolated models. This holistic approach ensures that clinical workflows and radiologist reviews work in harmony to enhance patient care.

Paul Hérent, Raidium's Chief Medical Officer, expressed enthusiasm over Dr. Langlotz’s appointment, stating, “Curtis has spent his career on the questions that matter most to us—how radiologists communicate what they find and how AI can find its right place in the reading room.” With Dr. Langlotz on board, the company aims to design technology tailored to the workflows of practicing radiologists, ensuring clinical professionals remain at the forefront of decision-making.

Additionally, Raidium will host a webinar titled, “Usage and Perspectives of AI in Radiology,” on November 10 at 8 a.m. CST, where Dr. Langlotz will contribute to critical discussions surrounding the future of AI in the field. Interested participants can register for this insightful session at Raidium's official site.

As Raidium continues to innovate with its AI-native radiology solutions and groundbreaking imaging tools, the collaboration with Dr. Langlotz signifies a commitment to enhancing the accuracy and efficiency of radiological practices. This partnership not only showcases the integration of advanced technologies in medicine but also reinforces the notion that radiologists will always play a crucial role in patient care.

The ongoing evolution in radiology driven by AI presents both challenges and opportunities, and with leaders like Dr. Langlotz steering these advancements, the future looks promising for practitioners and patients alike. Raidium stands at the forefront of this transformation, harnessing AI to redefine how radiology supports the broader medical community.

Through partnerships focusing on responsible development and validation, the integration of AI into radiology aims to improve workflows while ensuring that patients receive the highest standard of care. As this field continues to advance, the insights and guidance provided by experts like Dr. Langlotz will be essential in navigating the complexities of AI in health care.