Evidence map›Paper›PMID 32963749›Full record

SynthesisJournal of healthcare engineering2020

Augmented Reality Interface for Complex Anatomy Learning in the Central Nervous System: A Systematic Review.

Rahmita Wirza, Shah Nazir, Habib Ullah Khan, Iván García-Magariño, Rohul Amin

RetractedAbstract readSystematic ReviewRetracted Publication
In one paragraph

Synthesis in Journal of healthcare engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Rahmita WirzaDepartment of Multimedia, Faculty of Computer Science and Information Technology, University Putra Malaysia, Seri Kembangan, Malaysia.ORCID 0000-0002-9168-2451
Shah NazirDepartment of Computer Science, University of Swabi, Ambar, Khyber Pakhtunkhwa 23430, Pakistan.ORCID 0000-0003-0126-9944
Habib Ullah KhanDepartment of Accounting and Information System, College of Business and Economics, Qatar University, Doha 2713, Qatar.ORCID 0000-0001-8373-2781
Iván García-MagariñoDepartment of Software Engineering and Artificial Intelligence, Complutense University of Madrid, Madrid, Spain.
Rohul AminDepartment of Mathematics, University of Peshawar, Peshawar, Khyber Pakhtunkhwa 25120, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The medical system is facing the transformations with augmentation in the use of medical information systems, electronic records, smart, wearable devices, and handheld. The central nervous system function is to control the activities of the mind and the human body. Modern speedy development in medical and computational growth in the field of the central nervous system enables practitioners and researchers to extract and visualize insight from these systems. The function of augmented reality is to incorporate virtual and real objects, interactively running in a real-time and real environment. The role of augmented reality in the central nervous system becomes a thought-provoking task. Gesture interaction approach-based augmented reality in the central nervous system has enormous impending for reducing the care cost, quality refining of care, and waste and error reducing. To make this process smooth, it would be effective to present a comprehensive study report of the available state-of-the-art-work for enabling doctors and practitioners to easily use it in the decision making process. This comprehensive study will finally summarise the outputs of the published materials associate to gesture interaction-based augmented reality approach in the central nervous system. This research uses the protocol of systematic literature which systematically collects, analyses, and derives facts from the collected papers. The data collected range from the published materials for 10 years. 78 papers were selected and included papers based on the predefined inclusion, exclusion, and quality criteria. The study supports to identify the studies related to augmented reality in the nervous system, application of augmented reality in the nervous system, technique of augmented reality in the nervous system, and the gesture interaction approaches in the nervous system. The derivations from the studies show that there is certain amount of rise-up in yearly wise articles, and numerous studies exist, related to augmented reality and gestures interaction approaches to different systems of the human body, specifically to the nervous system. This research organises and summarises the existing associated work, which is in the form of published materials, and are related to augmented reality. This research will help the practitioners and researchers to sight most of the existing studies subjected to augmented reality-based gestures interaction approaches for the nervous system and then can eventually be followed as support in future for complex anatomy learning.

Indexed as

Augmented RealityGesturesLearningCentral Nervous SystemDecision MakingHumansImage Processing, Computer-AssistedMachine LearningNeuroimagingReproducibility of ResultsUser-Computer Interface

Identifiers

PMID32963749
PMCPMC7501559

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.