Evidence map›Paper›PMID 34249300›Full record

ReviewJournal of healthcare engineering2021

Remote Care Assistance in Emergency Department Based on Smart Medical.

Chengli Zhou, Juan Hu, Ni Chen

RetractedOpen access · hybridAbstract readReviewRetracted Publication
In one paragraph

Review in Journal of healthcare engineering, 2021. 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 It has been retracted, and should not be counted.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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 21% 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, 11 citations in OpenAlex.

  1. Trial
  2. Article
  3. Artificial Intelligence in Medicine and Dentistry.Acta stomatologica Croatica · 2023
    Review
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Chengli ZhouEmergency Department, Southwest Medical University, Luzhou 646000, Sichuan, China.
Juan HuEmergency Department, Southwest Medical University, Luzhou 646000, Sichuan, China.
Ni ChenEmergency Department, Southwest Medical University, Luzhou 646000, Sichuan, China.ORCID 0000-0003-0787-6403
Southwest Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smart medical care is user-centric, medical information is the main line, and big data, Internet of Things, cloud computing, artificial intelligence, and other technologies are used to establish scientific and accurate information, as well as an efficient and reasonable medical service system. Smart medical plays an important role in alleviating doctor-patient conflicts caused by information asymmetry, regional health differences caused by irrational allocation of medical resources, and improving medical service levels. This article mainly introduces the remote care assistance system of emergency department based on smart medical and intends to provide some ideas and directions for the technical research of patients in emergency department receiving remote care. This paper proposes a research method for remote care assistance in emergency departments based on smart medical, including an overview of remote care based on smart medical, remote care sensor real-time monitoring algorithms based on smart medical, signal detection algorithms, and signal clustering algorithms for smart medical. Remote care in the emergency department assisted in research experiments. The experimental results show that 86.0% of patients like the remote care system based on smart medical studied in this paper.

Indexed as

Artificial IntelligenceCloud ComputingBig DataEmergency Service, HospitalHumansRemote Sensing Technology

Identifiers

PMID34249300
PMCPMC8238575
OpenAlexW3175906028

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.