Evidence map›Paper›PMID 40697312›Full record

ReviewSurgery in practice and science2025

Advancements and challenges in robotic surgery: A holistic examination of operational dynamics and future directions.

Abdullah Riad, Majed Hadid, Adel Elomri, Ahmad Al-Ansari, Mohamed Amine Rejeb, Marwa Qaraqe, Sarada Parsad Dakua, Abdel Rahman Jaber, Abdulla Al-Ansari, Omar M Aboumarzouk and 1 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Surgery in practice and science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Pooled it
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  13. Legal Frameworks for AI-driven Diagnostics and Robotic Surgery.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2025
    Review
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

11 authors.

Abdullah RiadDivision of Engineering Management and Decision Sciences, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.
Majed HadidDivision of Engineering Management and Decision Sciences, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.
Adel ElomriDivision of Engineering Management and Decision Sciences, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.
Ahmad Al-AnsariWeill Cornell Medicine-Qatar, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar.
Mohamed Amine RejebSurgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha 3050, Qatar.
Marwa QaraqeDivision of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.
Sarada Parsad DakuaSurgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha 3050, Qatar.
Abdel Rahman JaberSurgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha 3050, Qatar.
Abdulla Al-AnsariSurgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha 3050, Qatar.
Omar M AboumarzoukSurgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha 3050, Qatar.
Abdelfatteh El OmriSurgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha 3050, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In recent years, Robot-Assisted Surgeries (RAS) have advanced significantly, revolutionizing healthcare with better patient outcomes, faster recovery times, and greater surgical accuracy. However, challenges such as restricted maneuverability and communication issues persist, along with the need to evaluate surgeons' proficiency in RAS. Healthcare 5.0 seeks to enhance RAS by integrating technologies like advanced imaging, haptic feedback, and artificial intelligence. Objective: This paper explores the Operational Management of Robotic-Assisted Surgeries (OM-RAS) by analyzing recent research. It assesses surgical robotics operations, workflow optimization, performance enhancement, and skill assessment. Additionally, it examines challenges and gaps in the RAS domain, providing a comprehensive research overview. Methods: A comprehensive literature search was conducted across databases such as Scopus, Web of Science, and Google Scholar, covering publications up to the third quarter of 2023. Search terms were selected using scientific criteria and validated by experts, resulting in a substantial document collection. A rigorous screening process, aligned with PRISMA 2020 standards, filtered the selection to 50 research papers, forming the foundation for detailed investigation. Findings: OM-RAS is a multidimensional field influenced by emerging technologies that optimize workflows, enhance performance, and improve skill assessment in RAS. Despite superior outcomes, challenges such as implementation costs and seamless technology integration persist. Additionally, research gaps exist regarding RAS benefits, creating opportunities for efficiency enhancement in patient care. Further exploration of RAS procedure scheduling across different surgery types is essential. Conclusion: Integrating advanced technologies into RAS has improved surgical outcomes, shortened hospital stays, and enhanced working environments. This study advocates for a holistic multi-criteria decision-making approach, considering factors like kinematics, imaging, Internet of Things/Tactile Internet (IoT/TI), and AI. It provides valuable insights, guiding future research and shaping OM-RAS studies.

Indexed as

Operations managementOptimizationPerformance enhancementRobotic surgeriesSkill assessment

Identifiers

PMID40697312
PMCPMC12280407

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.