Automated Computation of Therapies Using Failure Mode and Effects Analysis in the Medical Domain
This work addresses the problem of reducing manual effort for medical experts in analyzing FMEA models, but it appears incremental as it builds on existing FMEA and Markov decision process methods.
The paper tackles the manual analysis required in Failure Mode and Effects Analysis (FMEA) by developing a formal framework that automates the derivation of risk-reducing actions, specifically enabling automatic planning and acting in FMEA models. It demonstrates that this approach can automatically derive optimal therapies for patient treatment, though no concrete numbers are provided.
Failure mode and effects analysis (FMEA) is a systematic approach to identify and analyse potential failures and their effects in a system or process. The FMEA approach, however, requires domain experts to manually analyse the FMEA model to derive risk-reducing actions that should be applied. In this paper, we provide a formal framework to allow for automatic planning and acting in FMEA models. More specifically, we cast the FMEA model into a Markov decision process which can then be solved by existing solvers. We show that the FMEA approach can not only be used to support medical experts during the modelling process but also to automatically derive optimal therapies for the treatment of patients.