Healthcare organisations are often encouraged to learn from other industries in order to
develop proactive and rigorous safety management practices. In the UK safety–critical …

Machine Learning (ML) is now used in a range of systems with results that are reported to
exceed, under certain conditions, human performance. Many of these systems, in domains …

The use of safety cases in certification raises the question of assurance argument sufficiency
and the issue of confidence (or uncertainty) in the argument's claims. Some researchers …

Computational techniques that build models to correctly assign chemical compounds to
various classes of interest have many applications in pharmaceutical research and are used …

We discuss current trends in the development and use of high-confidence medical cyber-
physical systems (MCPS). These trends, including increased reliance on software to deliver …

Argument-based assurance cases, often represented and organized using graphical
argument structures, are increasingly being used in practice to provide assurance to …

We describe dynamic safety cases, a novel operationalization of the concept of through-life
safety assurance, whose goal is to enable proactive safety management. Using an example …

There is increasing interest in the application of machine learning (ML) technologies to
safety-critical cyber-physical systems, with the promise of increased levels of autonomy due …

Assurance cases are used to demonstrate confidence in system properties of interest (eg
safety and/or security). A number of system assurance approaches are adopted by …

Health care is under tremendous pressure regarding efficiency, safety, and economic
viability. It has responded by adopting techniques that have been useful in other industries …