Evidence map›Paper›PMID 39776281›Full record

SynthesisJournal of robotic surgery2025

Revolutionizing surgery: AI and robotics for precision, risk reduction, and innovation.

Jack Ng Kok Wah

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  12. Swine model for total laryngectomy training: assessment of the face, content, and construct validity.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025
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  19. Design and Performance of a Neurosurgery Assisting Device.Biomimetics (Basel, Switzerland) · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Jack Ng Kok WahMultimedia University, Cyberjaya, Malaysia. ngkokwah@mmu.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence and robotics are revolutionizing surgical practices by enhancing precision, efficiency, and patient outcomes. With global healthcare systems increasingly adopting AI-driven technologies, the integration of robotics in surgery addresses critical challenges such as surgical accuracy, minimally invasive techniques, and healthcare accessibility. However, disparities in access and ethical concerns regarding automation persist globally, necessitating a balanced discourse on these advancements. The primary objective of the review is to explore the intersection of AI and robotic technologies in surgical practices, highlighting key innovations, their impact on precision medicine, and future trajectories. The novelty of the review lies in synthesizing findings across diverse surgical specialties, including urology, plastic surgery, ophthalmology, and pediatric surgery, to provide a comprehensive understanding of AI's transformative role. The systematic review evaluates the integration of AI and robotics in surgery, synthesizing studies published in 2024. It follows PRISMA guidelines for study selection, data extraction, and synthesis. The review assesses surgical specialties, AI technologies, and outcomes like accuracy, recovery, and complications, ensuring methodological rigor and transparency. The findings indicate substantial advancements in AI-driven surgical systems, improving decision-making, reducing surgical errors, and facilitating personalized treatment strategies. Notable breakthroughs include AI-enhanced imaging, real-time data analysis, and automated robotic instruments, which collectively improve procedural efficiency and patient safety. The discussion emphasizes the critical implications of these innovations, particularly in advancing minimally invasive techniques and expanding surgical capabilities in complex procedures. However, challenges such as cost, ethical considerations, and the need for rigorous training protocols are highlighted as barriers to widespread adoption. The review underscores the implications for policymakers, healthcare institutions, and technology developers to address these barriers and promote equitable access to AI-driven surgical solutions. Limitations include the reliance on recent studies, necessitating long-term evaluations of clinical outcomes. Future research should focus on integrating AI with emerging technologies like augmented reality, fostering interdisciplinary collaboration, and addressing socio-ethical dimensions to fully realize the potential of AI in surgical advancements.

Indexed as

Artificial IntelligencePrecision MedicineRobotic Surgical ProceduresHumansInventionsAI-driven surgical systemsArtificial intelligence in healthcareMinimally invasive surgeryRobotics in surgerySurgical precision and efficiency

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.