Dr William Marsh
Medical Decision Support Models: Data, Knowledge and Evidence
Can data be used for decision-making? In many applications there are not enough data, key values are not directly observed or the problem requires reasoning about change. In these cases, it is better to combine data and knowledge for building a decision model.
Many medical decision problems fit this pattern. However, given the long history of clinical trials, clinicians are reluctant to assume an understanding of causes even when trials are completely impractical. Recent work on decision making in trauma surgery has shown the potential of causal models implemented using Bayesian networks. However, there are still many challenges before the use of these models can become routine.
Safety, Reliability And Risk: Modelling Accidents & Incident Causes
Analysing what can go wrong is fundamental for assessing risk in safety systems. Existing approaches have a number of deficiencies: (1) human behaviour and technical failures are poorly integrated (2) model created for system approval are often not used when a system is in operation (3) information on incidents and procedural compliance is not used to update risks.
The aim of the research is to extend existing accident-based modelling techniques to resolve these problems. Recent work has proposed a new model structure using a Bayesian network for causal modelling from accident / incident data, with the aim of predicting the likely safety / reliability improvement that would be achieved by changes in the operation of a system at a specific location.
Industry Training IEC 61508, Software Safety
Consultancy in systems and software safety Assignments for ERA Ltd and Agena Ltd