Evidence map›Paper›PMID 35903720›Full record

ArticleFrontiers in robotics and AI2022

Personalizing Care Through Robotic Assistance and Clinical Supervision.

Alessandra Sorrentino, Laura Fiorini, Gianmaria Mancioppi, Filippo Cavallo, Alessandro Umbrico, Amedeo Cesta, Andrea Orlandini

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Automated planning and scheduling in robot-aided rehabilitation: a review.Journal of neuroengineering and rehabilitation · 2025
    Review
  2. Article
  3. Article
  4. 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

7 authors.

Alessandra SorrentinoScuola Superiore Sant'Anna, Pisa, Italy.
Laura FioriniDepartment of Industrial Engineering, University of Florence, Florence, Italy.
Gianmaria MancioppiScuola Superiore Sant'Anna, Pisa, Italy.
Filippo CavalloScuola Superiore Sant'Anna, Pisa, Italy.
Alessandro UmbricoCNR-Institute of Cognitive Sciences and Technologies (CNR-ISTC), Rome, Italy.
Amedeo CestaCNR-Institute of Cognitive Sciences and Technologies (CNR-ISTC), Rome, Italy.
Andrea OrlandiniCNR-Institute of Cognitive Sciences and Technologies (CNR-ISTC), Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

By 2030, the World Health Organization (WHO) foresees a worldwide workforce shortfall of healthcare professionals, with dramatic consequences for patients, economies, and communities. Research in assistive robotics has experienced an increasing attention during the last decade demonstrating its utility in the realization of intelligent robotic solutions for healthcare and social assistance, also to compensate for such workforce shortages. Nevertheless, a challenge for effective assistive robots is dealing with a high variety of situations and

Indexed as

automated planning (AP)human–robot interaction (HRI)knowledge representation and reasoning (KRR)socially assistive robot (SAR)user modeling (UM)

Identifiers

PMID35903720
PMCPMC9315221

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.