ArticleNPJ digital medicine2025
Digitalization of surgical features improves surgical accuracy via surgeon guidance and robotization.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Artificial Intelligence and the Ethical Foundations of Cardiothoracic Surgery: Evidence, Accountability, and the Limits of Delegated Judgment.Medical sciences (Basel, Switzerland) · 2026Review
- Application of 5G technology in remote robotic surgery: a comprehensive assessment of system architecture, clinical benefits, and future challenges.Journal of robotic surgery · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
24 authors.
Funding
Abstract
The evolution of surgical techniques aims to augment surgeons' capabilities through digital guidance and robotization for higher precision and consistency. Currently, surgeries heavily rely on surgeon's experience and visual judgment, causing operation variations. Artificial intelligence (AI) offers a solution by extracting and digitizing surgical trajectories and features from videos to provide digital guidance. In this study, we collected 17,538 videos of capsulorhexis, a crucial step in cataract surgery, to create an AI-driven system named Meta Surgery (MetaS). MetaS evaluates and identifies ideal cases, extracts their digital characteristics, and fits an optimal capsulorhexis path in real-time during surgery. Surgeons performed capsulorhexis benefited from MetaS's guidance and a lens caliper, which increased the rate of ideal capsulorhexis by ~40%. Additionally, these digital features enabled a surgical robot to perform precise capsulorhexis autonomously in porcine eyes. This approach augments surgeons' surgical skills and paves the way for the autonomous operation of surgical robots.
Identifiers
What 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.