Evidence map›Paper›PMID 36611599›Full record

ArticleHealthcare (Basel, Switzerland)2023

IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database.

Md Harun-Ar-Rashid, Oindrila Chowdhury, Muhammad Minoar Hossain, Mohammad Motiur Rahman, Ghulam Muhammad, Salman A AlQahtani, Mubarak Alrashoud, Abdulsalam Yassine, M Shamim Hossain

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 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.

  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

9 authors.

Md Harun-Ar-RashidDepartment of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail 1902, Bangladesh.ORCID 0000-0002-2734-1492
Oindrila ChowdhuryDepartment of Computer Science and Engineering, American International University-Bangladesh (AIUB), Dhaka 1229, Bangladesh.
Muhammad Minoar HossainDepartment of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail 1902, Bangladesh.
Mohammad Motiur RahmanDepartment of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail 1902, Bangladesh.ORCID 0000-0003-4417-8276
Ghulam MuhammadDepartment of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.ORCID 0000-0002-9781-3969
Salman A AlQahtaniDepartment of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.ORCID 0000-0003-1233-1774
Mubarak AlrashoudDepartment of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
Abdulsalam YassineDepartment of Software Engineering, Lakehead University, 955 Oliver Road, Thunder Bay, ON P7B 5E1, Canada.
M Shamim HossainDepartment of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.ORCID 0000-0001-5906-9422

Funding

Researchers Supporting Project number (RSP-2021/32), King Saud University, Riyadh, Saudi Arabia RSP-2021/32
6 · The paper itself

Abstract

In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data.

Indexed as

Globally Unique Identifier (GUID)Health Level Seven (HL7)Internet of Things (IoT)Message Queuing Telemetry Transport (MQTT)Minimal Low Layer Protocol (MLLP)RSPI3 (Raspberry Pi 3)ULSM (Ultrasound Machine)

Identifiers

PMID36611599
PMCPMC9819388

What OpenQuestion holds

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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.