Artificial Intelligence & Machine Learning in Medical Device

AI refers to the ability of machines to perform tasks that normally require human intelligence – for example, recognizing patterns, learning from experience, drawing conclusions, making predictions, or taking action – whether digitally or as the smart software behind autonomous physical systems 

As of right now, there is no globally recognized standard regarding AI & ML in Medical Devices of Healthcare.

There are multiple working groups, developing standards for all industries:  Foundational standards (terminology, framework); Big Data (vocabulary, reference architecture); Trustworthiness (risk, robustness, bias); Use cases & applications; AI Governance.

Whether using a predictive (Waterfall; V- model) or adaptive methodology (Agile), it is imperative that the following processes and their corresponding outputs to be incorporated in the SaMD Development:

• Software development planning (SDP)
• Requirements analysis
• SaMD architectural design
• Software unit implementation and verification
• Software integration and integration testing
• SaMD verification and validation
• Problem resolution
• Configuration management
• SaMD release & maintenance
• SaMD Design Traceability
• Risk Management Activities

The European Commission put forward a European approach to Artificial Intelligence and Robotics. It deals with technological, ethical, legal, and socio-economic aspects to boost the EU's research and industrial capacity and to put AI at the service of European citizens and the economy. 

The European Commission published a White Paper aiming to foster a European ecosystem of excellence and trust in AI and a Report on the safety and liability aspects of AI. The White Paper proposes:

• Measures that will streamline research, foster collaboration between the Member States and increase investment into AI development and deployment;
• Policy options for a future EU regulatory framework that would determine the types of legal requirements that would apply to relevant actors, with a particular focus on high-risk applications.