The standards roadmap that will help bring AI and machine learning into healthcare
|How far have we come in deploying Artificial Intelligence (AI) and Machine Learning (ML) technology in healthcare?
BSI’s Standards Landscape Report SAFR – AI and Machine Learning in the Healthcare Domain gives a quantitative analysis of current and relevant standards in health software, particularly those that relate to AI and ML.
The SAFR (Safety Assurance FRamework for Machine Learning in the Healthcare Domain) is a project that is being funded through the AAIP (Assuring Autonomy International Programme) that aims to establish assurance guidance and resources to support the safe development and use of AI enabled health systems.
Why is the Standards Landscape Report needed?
Recent advances mean that AI and ML is now being used for a whole host of new applications, from condition monitoring that enables early intervention, to streamlined drug discovery that cuts time to market and costs. However, the technology also raises issues around patient safety, AI performance, and system security. This is especially true in the health sector where multiple organisations are responsible for regulation.
A safety assurance framework for AI and ML in healthcare will support the industry and healthcare services to meet regulatory and patient safety obligations. Consensus standards will play a central role by setting an agreed specification that should be met and offering examples of best practice and guidance to help organisations meet the requirements.
The Standards Landscape Report, SAFR – AI and Machine Learning in the Healthcare Domain provides a comprehensive overview of the standards landscape in the UK, Europe and internationally. The aim is to make it easy to identify the standards that exist from the perspective of medical device software, health IT and AI/ML. The report is an important step in developing the much-needed safety assurance framework.