Evidence map›Paper›PMID 35070382›Full record

ReviewJournal of thoracic disease2021

Artificial intelligence assisted display in thoracic surgery: development and possibilities.

Zhuxing Chen, Yudong Zhang, Zeping Yan, Junguo Dong, Weipeng Cai, Yongfu Ma, Jipeng Jiang, Keyao Dai, Hengrui Liang, Jianxing He

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of thoracic disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  19. Artificial Intelligence in Medicine: A Specialty-Level Overview of Emerging AI Trends.JSLS : Journal of the Society of Laparoendoscopic Surgeons
    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

10 authors.

Zhuxing Chen *Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Yudong Zhang *Department of Thoracic Surgery, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Zeping Yan *Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Junguo DongDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Weipeng CaiDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Yongfu MaDepartment of Thoracic Surgery, the First Medical Centre, Chinese PLA General Hospital, Beijing, China.
Jipeng JiangDepartment of Thoracic Surgery, the First Medical Centre, Chinese PLA General Hospital, Beijing, China.
Keyao DaiDepartment of Cardiothoracic Surgery, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Hengrui LiangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.
Jianxing HeDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this golden age of rapid development of artificial intelligence (AI), researchers and surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The popularity of low-dose computed tomography (LDCT) and the improvement of the video-assisted thoracoscopic surgery (VATS) not only bring opportunities for thoracic surgery but also bring challenges on the way forward. Preoperatively localizing lung nodules precisely, intraoperatively identifying anatomical structures accurately, and avoiding complications requires a visual display of individuals' specific anatomy for surgical simulation and assistance. With the advance of AI-assisted display technologies, including 3D reconstruction/3D printing, virtual reality (VR), augmented reality (AR), and mixed reality (MR), computer tomography (CT) imaging in thoracic surgery has been fully utilized for transforming 2D images to 3D model, which facilitates surgical teaching, planning, and simulation. AI-assisted display based on surgical videos is a new surgical application, which is still in its infancy. Notably, it has potential applications in thoracic surgery education, surgical quality evaluation, intraoperative assistance, and postoperative analysis. In this review, we illustrated the current AI-assisted display applications based on CT in thoracic surgery; focused on the emerging AI applications in thoracic surgery based on surgical videos by reviewing its relevant researches in other surgical fields and anticipate its potential development in thoracic surgery.

Indexed as

Artificial intelligence (AI)computed tomography (CT)surgical videothoracic surgery

Identifiers

PMID35070382
PMCPMC8743398

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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.