Evidence map›Paper›PMID 42022480›Full record

ArticleIEEE transactions on medical robotics and bionics2026

Interdisciplinary Dialogues on Surgical Data Science: Revising Its Benefits for Surgical Stakeholders and Patients.

Marco Bombieri, Arnaud Huaulmé, Kevin Cleary, Stamatia Giannarou, Gernot Kronreif, Franziska Mathis-Ullrich, Evangelos Mazomenos, Krystel Nyangoh Timoh, Micha Pfeiffer, Marco A Zenati and 2 more

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Article in IEEE transactions on medical robotics and bionics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Marco BombieriDepartment of Engineering for Innovation Medicine, University of Verona, 37134 Verona, Italy.ORCID 0000-0002-8607-8495
Arnaud HuaulméUniversity of Rennes, INSERM, LTSI - UMR 1099, 35000 Rennes, France.ORCID 0000-0002-7844-5259
Kevin ClearySheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC 20010 USA.ORCID 0000-0001-9809-4823
Stamatia GiannarouHamlyn Centre for Robotic Surgery, Department of Surgery and Cancer, Imperial College London, SW7 2AZ London, U.K.ORCID 0000-0002-8745-1343
Gernot KronreifAustrian Center for Medical Innovation and Technology, 2700 Wiener Neustadt, Austria.ORCID 0000-0003-2675-2190
Franziska Mathis-UllrichLaboratory for Surgical Planning and Robotic Cognition, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany.ORCID 0000-0001-5239-5305
Evangelos MazomenosUCL Hawkes Institute, Department of Medical Physics and Biomedical Engineering, University College London, W1W 7TY London, U.K.ORCID 0000-0003-0357-5996
Krystel Nyangoh TimohUniversity of Rennes, INSERM, LTSI-UMR 1099, 35000 Rennes, France, Department of Obstetrics and Gynecology, Rennes Hospital, 35000 Rennes, France.ORCID 0000-0003-4751-9080
Micha PfeifferNational Center for Tumor Diseases (NCT/UCC), German Cancer Research Center (DKFZ), Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, 01069 Dresden, Germany, and also with Helmholtz-Zentrum Dresden-Rossendorf (HZDR), 01328 Dresden, Germany.ORCID 0000-0001-9822-8641
Marco A ZenatiDivision of Cardiac Surgery, Brigham and Women's Hospital, Boston, MA 02115 USA, Department of Surgery, Harvard Medical School, Boston, MA 02115 USA, Department of Computer Science/DISI, University of Trento, 38123 Povo, Italy.ORCID 0000-0001-7139-0323
Paolo FioriniDepartment of Engineering for Innovation Medicine, University of Verona, 37134 Verona, Italy.ORCID 0000-0002-0711-8605
Pierre JanninUniversity of Rennes, INSERM, LTSI - UMR 1099, 35000 Rennes, France.ORCID 0000-0002-7415-071X

Funding

Developing Standardized Intraoperative Process Models to Enhance Surgical SafetyR01HL126896 · NHLBI · HARVARD MEDICAL SCHOOL · PI ZENATI, MARCO A. · 2016 to 2023
$3.7M
NHLBI NIH HHS R01 HL126896
6 · The paper itself

Abstract

Recent advancements in data science and robotic surgery have introduced significant opportunities and challenges in the field of healthcare. To assess their implications, a multidisciplinary panel of experts in medicine and computer science convened to evaluate the potential benefits, risks, and ethical considerations associated with these technologies. The discussion addressed critical topics, including the role of Artificial Intelligence (AI) in enhancing surgical decision-making, the integration of robotics to improve procedural precision, and the broader socioeconomic and psychological impacts on patients and their families. Particular attention was given to the perspectives of key surgical stakeholders, including healthcare professionals and institutions, as well as the implications for equity and accessibility in surgical care. This paper presents a synthesis of the key outcomes from the deliberations. By identifying research gaps and proposing strategic directions, the findings aim to serve as a foundational resource for future investigations and innovations in data-driven and robotic-assisted surgery.

Indexed as

robotic-assisted surgerySurgical data sciencesurgical stakeholders

Identifiers

PMID42022480
PMCPMC13099167

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Registered trials

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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.