Evidence map›Paper›PMID 40636458›Full record

ReviewiLIVER2025

Integrating mixed reality, augmented reality, and artificial intelligence in complex liver surgeries: Enhancing precision, safety, and outcomes.

Xianxing Wang, Jiali Yang, Beichuan Zhou, Li Tang, Yongxing Liang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in iLIVER, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. 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

5 authors.

Xianxing WangInstitute of Hepatopancreatobiliary Surgery, Chongqing General Hospital, Chongqing University, Chongqing 401147, China.
Jiali YangInstitute of Hepatopancreatobiliary Surgery, Chongqing General Hospital, Chongqing University, Chongqing 401147, China.
Beichuan ZhouApplication and Popularization Institute, China Academy of Industrial Internet, Beijing 100015, China.
Li TangInstitute of Hepatopancreatobiliary Surgery, Chongqing General Hospital, Chongqing University, Chongqing 401147, China.
Yongxing LiangApplication and Popularization Institute, China Academy of Industrial Internet, Beijing 100015, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatobiliary surgeries, particularly hepatectomy and liver transplantation, are critical interventions for hepatic malignancies and end-stage liver diseases. These complex procedures face challenges due to the liver's intricate anatomy and vascularization. The integration of Mixed Reality (MR), Augmented Reality (AR), and Artificial Intelligence (AI) is increasingly enhancing the precision, safety, and outcomes of these surgeries. MR and AR improve visualization of anatomical structures, assist in preoperative planning, and support patient education through immersive 3D models. AI-driven technologies provide real-time intraoperative feedback and navigation, optimizing surgical decisions and minimizing risks. Postoperatively, these technologies aid in patient education and recovery management, ultimately improving outcomes. This review explores the applications of MR, AR, and AI in liver surgeries and their potential to transform surgical practice by enhancing precision, safety, and patient engagement.

Indexed as

Artificial intelligenceAugmented realityEmerging technologiesHepatobiliary surgeryMixed realitySurgical precision and safety

Identifiers

PMID40636458
PMCPMC12209476

What Socratic 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 Socratic graph.