Evidence map›Paper›PMID 32682657›Full record

ArticleJournal of infection and public health2020

Secure and energy-efficient framework using Internet of Medical Things for e-healthcare.

Tanzila Saba, Khalid Haseeb, Imran Ahmed, Amjad Rehman

Open access · goldAbstract read
In one paragraph

Article in Journal of infection and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
10.0field-weighted citation impact, top 1% 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

14 citing papers in PubMed, 165 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. 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

4 authors at 3 institutions in 2 countries.

Tanzila SabaArtificial Intelligence & Data Analytics Lab (AIDA) CCIS Prince Sultan University Riyadh, 11586, Saudi Arabia. Electronic address: drstanzila@gmail.com.
Khalid HaseebIslamia College Peshawar, Peshawar, Pakistan. Electronic address: khalid.haseeb@icp.edu.pk.
Imran AhmedInstitute of Management Sciences, Peshawar, Pakistan. Electronic address: imran.ahmed@imsciences.edu.pk.
Amjad RehmanArtificial Intelligence & Data Analytics Lab (AIDA) CCIS Prince Sultan University Riyadh, 11586, Saudi Arabia. Electronic address: rkamjad@gmail.com.
Prince Sultan University · SAInstitute of Management Sciences Peshawar · PKIslamia College University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In various fields, the internet of things (IoT) gains a lot of popularity due to its autonomous sensors operations with the least cost. In medical and healthcare applications, the IoT devices develop an ecosystem to sense the medical conditions of the patients' such as blood pressure, oxygen level, heartbeat, temperature, etc. and take appropriate actions on an emergency basis. Using it, the healthcare-related data of patients is transmitted towards the remote users and medical centers for post-analysis. Different solutions have been proposed using Wireless Body Area Network (WBAN) to monitor the medical status of the patients based on low powered biosensor nodes, however, preventing increased energy consumption and communication costs are demanding and interesting problems. The issue of unbalanced energy consumption between biosensor nodes degrades the timely delivery of the patient's information to remote centers and gives a negative impact on the medical system. Moreover, the sensitive data of the patient is transmitting over the insecure Internet and prone to vulnerable security threats. Therefore, data privacy and integrity from malicious traffic are another challenging research issue for medical applications. This research article aims to a proposed secure and energy-efficient framework using Internet of Medical Things (IoMT) for e-healthcare (SEF-IoMT), which primary objective is to decrease the communication overhead and energy consumption between biosensors while transmitting the healthcare data on a convenient manner, and the other hand, it also secures the medical data of the patients against unauthentic and malicious nodes to improve the network privacy and integrity. The simulated results exhibit that the proposed framework improves the performance of medical systems for network throughput by 18%, packets loss rate by 44%, end-to-end delay by 26%, energy consumption by 29%, and link breaches by 48% than other states of the art solutions.

Indexed as

Internet of ThingsTelemedicineDelivery of Health CareEcosystemHumansPrivacyBiosensorsData securityEnergy efficiencyHealthcareHealth systemInternet of Medical Things (IoMT)

Identifiers

PMID32682657
PMCPMC7362861
OpenAlexW3042392478

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.