Evidence map›Paper›PMID 35831137›Full record

ArticleJournal of Korean Neurosurgical Society2023

Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review.

Kuchalambal Agadi, Asimina Dominari, Sameer Saleem Tebha, Asma Mohammadi, Samina Zahid

Open access · goldAbstract readScoping Review
In one paragraph

Article in Journal of Korean Neurosurgical Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. 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 at 3 institutions in 3 countries.

Kuchalambal AgadiDivision of Research and Academic Affairs, Larkin Health System, South Miami, FL, USA.
Asimina DominariDivision of Research and Academic Affairs, Larkin Health System, South Miami, FL, USA.
Sameer Saleem TebhaDivision of Research and Academic Affairs, Larkin Health System, South Miami, FL, USA.
Asma MohammadiDivision of Research and Academic Affairs, Larkin Health System, South Miami, FL, USA.
Samina ZahidDivision of Research and Academic Affairs, Larkin Health System, South Miami, FL, USA.
Larkin University · USAristotle University of Thessaloniki · GRJinnah Medical & Dental College · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

Indexed as

Artificial intelligenceCentral nervous system neoplasmsDisease managementNeurosurgery

Identifiers

PMID35831137
PMCPMC10641423
OpenAlexW4285390558

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.