Stanford AI leader Curtis Langlotz joins Raidium advisory board
Radiologist and Stanford University professor Curtis Langlotz has joined Raidium’s strategic advisory board, where he will advise the AI imaging company on validating and responsibly developing AI-assisted radiology reporting. He will also appear at a Raidium webinar on AI in radiology on November 10.
- Curtis Langlotz has joined Raidium’s strategic advisory board.
- He will advise on clinical validation and responsible AI-assisted reporting.
- Langlotz says radiologists should remain in control and be able to understand AI-generated drafts.
- Raidium will host a radiology AI webinar on November 10 at 8 a.m. CST.
- Langlotz joins strategic adviser Ludovic d’Apréa.
Advice focused on clinical validation
Raidium said Langlotz will advise on how its reporting technology is evaluated and developed around radiologists. The company is building tools for radiology and oncology imaging, and said his work with the board will focus on clinical validation and responsible development.
Langlotz is Professor of Radiology, Medicine, and Biomedical Data Science at Stanford University. He is also Senior Associate Vice Provost for Research at the university, a Senior Fellow at Stanford’s Institute for Human-Centered Artificial Intelligence, and Director of the Center for Artificial Intelligence in Medicine and Imaging.
His laboratory develops machine learning methods intended to improve the accuracy and efficiency of medical image interpretation by detecting disease early and reducing medical errors. The center he directs supports over 250 faculty at Stanford working on interdisciplinary machine learning research to improve clinical care.
Keeping radiologists in control
Langlotz said the radiology report is the way radiologists’ work reaches patients and the clinicians who care for them. He argued that AI reporting tools should allow radiologists to remain in control, understand how a draft was produced, and trust the report they sign.
“The important question now is how to build these tools so radiologists stay in control, can see how a draft was produced, and can trust what they sign,” Langlotz said in Raidium’s announcement.
According to Raidium, Langlotz has emphasized that trust in radiology AI depends on validating the full system. That includes the models, clinical workflows, and radiologist review process, rather than evaluating a single model in isolation. He will help Raidium apply that standard while it develops and evaluates its technology with clinical partners.
Raidium Chief Medical Officer Paul Hérent said Langlotz’s perspective would help the company build around how radiologists work, with clinicians in control at every step. Langlotz joins Ludovic d’Apréa, who became a strategic advisor in October.
Webinar will examine AI’s use in radiology
Raidium will host a webinar titled “Usage and Perspectives of AI in Radiology” on Tuesday, November 10, at 8 a.m. CST. Langlotz will join the discussion, and registration is open through the event link provided by the company.
Raidium describes itself as an AI-native radiology company combining a foundation model research lab with a unified, promptable AI viewer. It says its tools automate radiology workflows from indication to final report while keeping the radiologist in control at every step.
For oncology, the company says its Raidium Read platform automates RECIST imaging endpoints for research and clinical trials use. Raidium operates globally, with offices in Paris, France, and Silicon Valley, USA.
Langlotz’s appointment gives Raidium an adviser whose stated focus is the evaluation of AI as part of clinical work, rather than only the performance of an individual model. For users, the company’s announcement points to greater emphasis on review, transparency, and clinical validation as its reporting tools are developed with clinical partners.
