Key Points Question Is clinician diagnostic performance associated with the use of machine learning–based clinical decision support systems? Findings In this systematic review of 37 studies, no robust evidence was found to suggest an association between the use of machine learning–based clinical algorithms to support rather than replace human decision-making and improved clinician diagnostic performance. Meaning Caution should be observed when estimating the current ability of machine learning algorithms to affect patient care, and emphasis on the evaluation of the human-computer interaction is needed.

Objective: To define reporting standards for IDEAL format studies. Background:The IDEAL Framework and Recommendations establish an integrated pathway for evaluation of new surgical techniques and complex therapeutic technologies. However guidance on implementation has been incomplete, and incorrect use is commonly seen. We Conclusions: Participants familiar with IDEAL called for reporting guidelines for studies in all IDEAL stages except stage 3. The checklists developed have the potential to improve standards of reporting and thereby advance the quality of research on surgery and complex interventions and technologies, but require further evaluation in use.

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