Evidence map›Paper›PMID 35236504›Full record

ArticleArthroplasty (London, England)2022

Augmented Intelligence in Joint Replacement Surgery: How can artificial intelligence (AI) bridge the gap between the man and the machine?

Vaibhav Bagaria, Anjali Tiwari

Abstract read
In one paragraph

Article in Arthroplasty (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
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

2 authors.

Vaibhav BagariaDepartment of Orthopaedic Surgery, Sir H.N. Reliance Foundation Hospital and Research Center, Girgaon, Mumbai, Maharashtra, India. bagariavaibhav@gmail.com.ORCID http://orcid.org/0000-0002-3009-3485
Anjali TiwariDepartment of Orthopaedic Surgery, Sir H.N. Reliance Foundation Hospital and Research Center, Girgaon, Mumbai, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robot-assisted arthroplasty is likely to grow exponentially in the years to come. While most surgeons recognize their superiority in refining alignment and improving component positioning accuracy, the universal adaptability of robots remains slow due to certain technological and behavioural gaps. Endoprosthesis robots currently suffer from increased reaction time, lack of natural adaptation to the surgeon's abilities, and unavailability and inapplicability in different surgical contexts. As humans and machines have to move forward into the next phase of their relationship, robots enabled with artificial intelligence (AI) may become more advanced and an alternative to overcome existing challenges like cost, training, and improve performance based on feedback provided by surgeons. Augmented intelligence is perhaps a more apt word than artificial, as it reflects more human-machine fusion and several areas are already proactively adopting the terminology. Arthroplasty robots can benefit from AI by using computer vision models, applying sensors, and integrating feedback and loop execution. All of this would help achieve a technical superiority to the surgeon alone. This brief perspective on how humans and machines are likely to benefit from the integration of AI outlines the technical side of this enablement.

Indexed as

ArthroplastyArtificial intelligenceInterfaceMachine learningRobotics

Identifiers

PMID35236504
PMCPMC8808959

What OpenQuestion holds

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LicenceCC BY
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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.