Evidence map›Paper›PMID 36749675›Full record

ArticleHealthcom. International Conference on e-Health Networking, Applications and Services2022

MDT-based Intelligent Route Selection for 5G-Enabled Connected Ambulances.

Muhammad Umar Bin Farooq, Marvin Manalastas, Haneya Qureshi, Yongkang Liu, Ali Imran, Mohamad Omar Al Kalaa

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Healthcom. International Conference on e-Health Networking, Applications and Services, 2022. 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
0.5field-weighted citation impact, top 38% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. 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

6 authors at 4 institutions in 1 country.

Muhammad Umar Bin FarooqAI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, USA.
Marvin ManalastasAI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, USA.
Haneya QureshiAI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, USA.
Yongkang LiuCenter for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Ali ImranAI4Networks Research Center, School of Electrical & Computer Engineering, University of Oklahoma, USA.
Mohamad Omar Al KalaaCenter for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, USA.
RealNetworks (United States) · USUnited States Food and Drug Administration · USCenter for Devices and Radiological Health · USUniversity of Oklahoma · US

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

The fifth generation of cellular network (5G) can facilitate in-ambulance patient monitoring, diagnosis, and treatment by a remote specialist. However, 5G coverage and link quality can vary in time and location. The ambulance route selection can help meet the communication requirements of the in-ambulance applications. In this paper, we propose an innovative ambulance route selection framework which combines the communication requirements along with the network coverage and resources. The framework leverages the minimization of drive test (MDT) data to estimate the network coverage along the ambulance routes. To address the uneven distribution of location-based user-generated MDT data, we examine the performance and trustworthiness of several interpolation techniques to enrich the global MDT map for route selection. A simulated analysis shows that the proposed framework can dynamically adapt to varying application requirements as well as rapidly changing network conditions such as outages. Results also reveal that nearest neighbor and kriging interpolation techniques help complement the proposed framework by addressing the data sparsity problem.

Indexed as

5GConnected ambulanceMDT reportsmart routing

Identifiers

PMID36749675
PMCPMC9846196
OpenAlexW4312955053

What OpenQuestion holds

Textmetadata
LicenceTDM
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.