Evidence map›Paper›PMID 31187605›Full record

ReviewBirth defects research2020

Regenerative robotics.

Dana D Damian

Open access · hybridAbstract readReview
In one paragraph

Review in Birth defects research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. The automaton as a surgeon: the future of artificial intelligence in emergency and general surgery.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2021
    Review
  2. Regenerative robotics.Birth defects research · 2020
    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

1 author at 1 institution in 1 country.

Dana D DamianDepartment of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, United Kingdom.ORCID 0000-0002-0595-0182
University of Sheffield · GB

Funding

Engineering and Physical Sciences Research Council EP/S021035/1
6 · The paper itself

Abstract

Congenital diseases requiring reconstruction of parts of the gastrointestinal tract, skin, or bone are a challenge to alleviate especially in rapidly growing children. Novel technologies may be the answer. This article presents the state-of-art in regenerative robotic technologies, which are technologies that assist tissues and organs to regenerate using sensing and mechanotherapeutical capabilities. It addresses the challenges in the development of such technologies, among which are autonomy and fault-tolerance for long-term therapy as well as morphological conformations and compliance of such devices to adapt to gradual changes of the tissues in vivo. The potential as medical devices for delivering therapies for tissue growth and as tools for scientific exploration of regenerative mechanisms is also discussed.

Indexed as

Guided Tissue RegenerationHumansRegenerationRegenerative MedicineRoboticsmechanotherapyrobotic implantssoft robotstissue growthtissue regeneration

Identifiers

PMID31187605
PMCPMC7006820
OpenAlexW4251797859

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.