Guideline for software life cycle in health informatics

The long-lasting trend of medical informatics is to adapt novel technologies in the medical context. In particular, incorporating artificial intelligence to support clinical decision-making can significantly improve monitoring, diagnostics, and prognostics for the patient's and medic's sake. However, obstacles hinder a timely technology transfer from research to the clinic. Due to the pressure for novelty in the research context, projects rarely implement quality standards. Here, we propose a guideline for academic software life cycle processes tailored to the needs and capabilities of research organizations. While the complete implementation of a software life cycle according to commercial standards is not feasible in scientific work, we propose a subset of elements that we are convinced will provide a significant benefit while keeping the effort within a feasible range. Ultimately, the emerging quality checks for academic software development can pave the way for an accelerated deployment of academic advances in clinical practice.