ArticleTrauma surgery & acute care open2026
Artificial Intelligence in Surgical Care: A Point-Counterpoint Analysis.
Article in Trauma surgery & acute care open, 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
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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.
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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.
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Authors and funding
5 authors.
Funding
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Abstract
Artificial intelligence (AI) integration in surgical care represents a paradigm shift with significant potential benefits and risks. This point-counterpoint debate examined the proposition that AI improves surgical patient care. A structured debate format featuring Dr Divya Kewalramani (pro-AI) and Dr Michael Aboutanos (con-AI) explored the current state, opportunities, and challenges of AI implementation in surgical practice. The pro-AI argument emphasized addressing surgical care gaps through predictive analytics, supply chain optimization, and enhanced postoperative monitoring. The con-AI position highlighted concerns about data biases, validation deficits, hallucinations, and implementation risks. While AI demonstrates potential to improve surgical care, substantial challenges remain regarding validation, inclusivity, and oversight. Responsible adoption requires robust evaluation frameworks, diverse datasets, and continuous postimplementation monitoring.
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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.