Claims

Trainees and trainers hold mixed views on AI-generated heat maps for postoperative coaching

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? In the single qualitative study, 73% of trainees and trainers strongly agreed that AI-generated heat maps showing safe and unsafe dissection could be effective for postoperative coaching and feedback, but 40% reported they would not use it routinely. → Dick L 2024

Evidence

Dick L 2024

Dick L, Boyle CP, Skipworth RJE, Smink DS, Tallentire VR, Yule S. (2024). Automated analysis of operative video in surgical training: scoping review. BJS Open. https://doi.org/10.1093/bjsopen/zrae124

q2 · i? · review · r2

The review reports the one included qualitative study (Hameed et al.), which surveyed trainees and trainers on AI-generated heat maps for laparoscopic cholecystectomy. It reports mixed opinions, with some raising "concerns over potential dependence on it for making intraoperative decisions".

"Trainees and trainers strongly agreed (73%) that their use after surgery for coaching and feedback could be effective. Most suggested that heat maps should be incorporated in the surgical training curriculum, particularly for those at an earlier stage in training. However, 40% reported that, even if readily available, they would not use it routinely."

Discussion

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