Evidence map›Paper›PMID 36854554›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2023

[Design and implementation of Internet of Things for emergency medical devices based on cloud-edge-device architecture].

Yong Fan, Hong Liang, Jipeng Sun, Boying Zhang, Haiyan Zhu, Desen Cao, Zhengbo Zhang, Kunlun He

Open access · greenAbstract readEnglish Abstract
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. [Design and implementation of the internet of medical things data platform based on cloud-edge-end architecture].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
    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

8 authors at 1 institution in 1 country.

Yong FanCenter for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Hong LiangCenter for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Jipeng SunCenter for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Boying ZhangDepartment of Medical Engineering, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Haiyan ZhuDepartment of Emergency, the First Medical Center, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Desen CaoDepartment of Medical Engineering, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Zhengbo ZhangCenter for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Kunlun HeMedical Big Data Research Center, Chinese PLA General Hospital, Beijing 100853, P. R. China.
Chinese PLA General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Internet of Things (IoT) technology plays an important role in smart healthcare. This paper discusses IoT solution for emergency medical devices in hospitals. Based on the cloud-edge-device architecture, different medical devices were connected; Streaming data were parsed, distributed, and computed at the edge nodes; Data were stored, analyzed and visualized in the cloud nodes. The IoT system has been working steadily for nearly 20 months since it run in the emergency department in January 2021. Through preliminary analysis with collected data, IoT performance testing and development of early warning model, the feasibility and reliability of the in-hospital emergency medical devices IoT was verified, which can collect data for a long time on a large scale and support the development and deployment of machine learning models. The paper ends with an outlook on medical device data exchange and wireless transmission in the IoT of emergency medical devices, the connection of emergency equipment inside and outside the hospital, and the next step of analyzing IoT data to develop emergency intelligent IoT applications.

Indexed as

Internet of ThingsInternetMachine LearningReproducibility of ResultsTechnologyEmergency medicineInternet of ThingsMedical devicesStreaming data

Identifiers

PMID36854554
PMCPMC9989756
OpenAlexW4322719457

What OpenQuestion holds

Textmetadata
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.