Commercialization of medical artificial intelligence technologies: challenges and opportunities.
Authors
Affiliations (5)
Affiliations (5)
- Division of Vascular Surgery, University of Toronto, Toronto, Ontario, Canada.
- Temerty Centre for Artificial Intelligence Research and Education in Medicine, University of Toronto, Toronto, Ontario, Canada.
- Faculty of Health Sciences & Sport, University of Stirling, Stirling, UK.
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK. [email protected].
- Department of Vascular Surgery, Oxford University Hospitals, NHS Foundation Trust, Oxford, UK. [email protected].
Abstract
Artificial intelligence (AI) is already having a significant impact on healthcare. For example, AI-guided imaging can improve the diagnosis/treatment of vascular diseases, which affect over 200 million people globally. Recently, Chiu and colleagues (2024) developed an AI algorithm that supports nurses with no ultrasound training in diagnosing abdominal aortic aneurysms (AAA) with similar accuracy as ultrasound-trained physicians. This technology can therefore improve AAA screening; however, achieving clinical impact with new AI technologies requires careful consideration of commercialization strategies, including funding, compliance with safety and regulatory frameworks, health technology assessment, regulatory approval, reimbursement, and clinical guideline integration.