Evidence map›Paper›PMID 35371874›Full record

ReviewCureus2022

Robotics and Artificial Intelligence in Endovascular Neurosurgery.

Javier Bravo, Arvin R Wali, Brian R Hirshman, Tilvawala Gopesh, Jeffrey A Steinberg, Bernard Yan, J Scott Pannell, Alexander Norbash, James Friend, Alexander A Khalessi and 1 more

Open access · diamondAbstract readReview
In one paragraph

Review in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.6field-weighted citation impact, top 6% of its field
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

15 citing papers in PubMed, 24 citations in OpenAlex.

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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

11 authors at 4 institutions in 2 countries.

Javier BravoNeurological Surgery, University of California San Diego, San Diego, USA.
Arvin R WaliNeurological Surgery, University of California San Diego, San Diego, USA.
Brian R HirshmanNeurological Surgery, University of California San Diego, San Diego, USA.
Tilvawala GopeshEngineering and Healthcare Technology, University of California San Diego Jacobs School of Engineering, San Diego, USA.
Jeffrey A SteinbergNeurological Surgery, University of California San Diego, San Diego, USA.
Bernard YanDepartment of Neurology, Royal Melbourne Hospital, Melbourne, AUS.
J Scott PannellNeurological Surgery, University of California San Diego, San Diego, USA.
Alexander NorbashNeurological Surgery, University of California San Diego, San Diego, USA.
James FriendEngineering and Healthcare Technology, University of California San Diego Jacobs School of Engineering, San Diego, USA.
Alexander A KhalessiNeurological Surgery, University of California San Diego, San Diego, USA.
David Santiago-DieppaNeurological Surgery, University of California San Diego, San Diego, USA.
The Royal Melbourne Hospital · AUUniversity of California, San Diego · USNeurological Surgery · USUniversity of San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of artificial intelligence (AI) and robotics in endovascular neurosurgery promises to transform neurovascular care. We present a review of the recently published neurosurgical literature on artificial intelligence and robotics in endovascular neurosurgery to provide insights into the current advances and applications of this technology. The PubMed database was searched for "neurosurgery" OR "endovascular" OR "interventional" AND "robotics" OR "artificial intelligence" between January 2016 and August 2021. A total of 1296 articles were identified, and after applying the inclusion and exclusion criteria, 38 manuscripts were selected for review and analysis. These manuscripts were divided into four categories: 1) robotics and AI for the diagnosis of cerebrovascular pathology, 2) robotics and AI for the treatment of cerebrovascular pathology, 3) robotics and AI for training in neuroendovascular procedures, and 4) robotics and AI for clinical outcome optimization. The 38 articles presented include 23 articles on AI-based diagnosis of cerebrovascular disease, 10 articles on AI-based treatment of cerebrovascular disease, two articles on AI-based training techniques for neuroendovascular procedures, and three articles reporting AI prediction models of clinical outcomes in vascular disorders of the brain. Innovation with robotics and AI focus on diagnostic efficiency, optimizing treatment and interventional procedures, improving physician procedural performance, and predicting clinical outcomes with the use of artificial intelligence and robotics. Experimental studies with robotic systems have demonstrated safety and efficacy in treating cerebrovascular disorders, and novel microcatheterization techniques may permit access to deeper brain regions. Other studies show that pre-procedural simulations increase overall physician performance. Artificial intelligence also shows superiority over existing statistical tools in predicting clinical outcomes. The recent advances and current usage of robotics and AI in the endovascular neurosurgery field suggest that the collaboration between physicians and machines has a bright future for the improvement of patient care. The aim of this work is to equip the medical readership, in particular the neurosurgical specialty, with tools to better understand and apply findings from research on artificial intelligence and robotics in endovascular neurosurgery.

Indexed as

ai and machine learningartificial intelligencecomputer-assisted diagnosisendovascularneurosurgeryrobotics

Identifiers

PMID35371874
PMCPMC8971092
OpenAlexW4220699841

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.