Reproducibility challenges in robotic surgery - Faragasso, Angela; Bonsignorio, Fabio (Frontiers in Robotics and AI, 2023)
Reproducibility of results is, in all research fields, the cornerstone of the scientific method and the minimum standard for assessing the value of scientific claims and conclusions drawn by other scientists. It requires a systematic approach and accurate description of the experimental procedure as well as data analysis which will allow other scientists to follow the steps described in the published work and obtain the "same results". In general and in different research contexts with "same" results, we mean different things. It can be almost identical measures in a fully deterministic experiment or "validation of an hypotheses" or statistically similar results in a non deterministic context. Unfortunately, it has been shown by systematic meta analysis studies that a lot of findings in fields like psychology, sociology, medicine, and economics don't hold up when other researchers try to replicate them. Many scientific fields are experiencing what is generally referred to as a "reproducibility crisis" which undermines the trust in published results, imposes a thorough revision of the methodology in scientific research and makes hard to progress. In general, reproducibility of experiments is not a mainstream practice in artificial intelligence and robotics research. Surgical robotics is no exception. There is the need of developing new tools and putting in place a community effort to allow the transition to more reproducible research and hence, faster progress in research. Reproducibility, replicability and benchmarking (operational procedures for the assessment and comparison of research results) are made more complex for medical robotics and surgical systems, due to patenting, safety and ethical issues. In this review paper we selected ten of the most relevant published manuscripts on surgical robotics to underline the problems related to reproducibility and replicability of the reported experiments with the aim of finding possible solutions to the challenges that limit the translation of many scientific researches into real-word applications and slow down research progress.