Evidence map›Paper›PMID 42422025›Full record

ReviewInnovation (Cambridge (Mass.))2026

Cooperative integrated surgical robots for high-performance targeted therapies.

Zhengyang Li, Zhaoyang Qi, Zehao Wu, Li Zhang, Qingsong Xu

Abstract readReview
In one paragraph

Review in Innovation (Cambridge (Mass.)), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Zhengyang LiDepartment of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macao SAR, China.
Zhaoyang QiDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin N.T., Hong Kong SAR, China.
Zehao WuDepartment of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macao SAR, China.
Li ZhangDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin N.T., Hong Kong SAR, China.
Qingsong XuDepartment of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macao SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The escalating demand for secure, precise, and high-performance targeted therapies has elevated surgical robots to a prominent position in the field of robotics and translational medicine research in recent decades. However, surgical robots with single functionality and isotropic configuration exhibit limitations in accomplishing intricate and multi-objective surgical tasks. With the rise of multi-agent intelligence, cooperative integrated surgical robots with multiple robotized instruments and imaging modalities, which can perform cooperative motions during autonomous operations, demonstrate great potential in dealing with multi-faceted intraoperative surgical tasks employing complementary functionalities, enhancing the efficacy of surgical procedures spatiotemporally. This review systematically outlines the recent advancements in this burgeoning field by defining the concept, key technologies, and representative breakthroughs while elaborating on the prospects for targeted therapies. We also elucidate the challenges and clinical feasibility of the current cooperative surgical robots and discuss the future directions for next-generation multi-functional solutions to expand biomedical application horizons.

Indexed as

cooperative robotsmedical intelligencesurgical robotstargeted therapy

Identifiers

PMID42422025
PMCPMC13343438

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.