Abstract:
Clinical Machine Learning (ML) is a rapidly-growing field due to the digitization of hospital records, recent advances in ML techniques, and the ability to leverage increasing computational power for large and complex models. The high stakes and often unintuitive nature of clinical data make effective collaboration between clinicians and ML researchers one of the most important aspects of working in this interdisciplinary space. However, there are few resources codifying best practices for collaboration on Clinical ML projects. In this paper, we interviewed 18 experts in the Clinical ML field and distilled their advice and experiences into a list of questions (a Clinical Collabsheet) ML scientists and clinicians can use to promote effective discussion when working on a new project. We intend this for a broad audience as checklist of discussion points to hit at a kickoff meeting. This resource will enable more successful partnerships in Clinical ML with improved interdisciplinary communication and organization.
