ReviewUnfallchirurgie (Heidelberg, Germany)2026
[Digital operating room-From dream to workflow].
Review in Unfallchirurgie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The challenging transformation of medicine in the twenty-first century, involving robotics, artificial intelligence (AI) and the digitalization of daily work routines, is hampered by bureaucratic hurdles, a shortage of skilled workers and socioeconomic pressures within an aging healthcare system. This article provides an overview of current possibilities and applications of AI in the (peri)operative care of trauma patients. Even before surgeons enter the operating room, preoperative AI planning tools could increase efficiency in the future. Intraoperatively, navigation and robotics are already well-established and improve precision. In the future, ambient AI and digital twins can be expected to also link perioperative data as well as optimizing workflows and making decisions. The AI-supported surgical documentation increasingly relieves the workload for physicians but it still poses risks and interoperability issues. Key hurdles for AI in the operating room remain data heterogeneity, a lack of standardization and costs. It is also important, especially in the operating room, that the ethical responsibility for controlling (semi)autonomous systems remains with humans.
Indexed as
Identifiers
42862343What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.