How far are vision-free medical robots from achieving trustworthy embodied intelligence?

Jiacheng Liu, Hong Zhang, Hao Wang, Shilong Han, Xu Chen, Xiaohang Nie, Jie Liu, Yichao Tang

Abstract readReview

In one paragraph

Review in iScience, 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

8 authors.

Jiacheng LiuShanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China.

Hong ZhangShanghai Innovation Institute, Shanghai, China.

Hao WangShanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China.

Shilong HanDepartment of Interventional and Vascular Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.

Xu ChenNational Clinical Research Center for Interventional Medicine, Interventional Medicine Innovation Alliance, Shanghai, China.

Xiaohang NieShanghai Innovation Institute, Shanghai, China.

Jie LiuSchool of Mechanical Engineering, Tongji University, Shanghai, China.

Yichao TangShanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Embodied Intelligence (EI) is rapidly reshaping the field of robotic surgery, enabling unprecedented levels of clinical precision while liberating surgeons from excessive cognitive and physical burdens. However, for "vision-free" surgical robots incapable of integrating direct visual sensing-such as endovascular robots and untethered swarms-their persistent reliance on external medical imaging fundamentally impedes their evolution toward safe and trustworthy EI-surgery.

Indexed as

direct visionembodied intelligencemedical roboticsmultimodal perception

Identifiers

PMID42894641

DOI10.1016/j.isci.2026.117416

PMCPMC13676698

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.