Evidence map›Paper›PMID 37430494›Full record

ArticleSensors (Basel, Switzerland)2023

Monitoring Acute Heart Failure Patients Using Internet-of-Things-Based Smart Monitoring System.

Nouf Abdullah Almujally, Turki Aljrees, Oumaima Saidani, Muhammad Umer, Zaid Bin Faheem, Nihal Abuzinadah, Khaled Alnowaiser, Imran Ashraf

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
12.1field-weighted citation impact, top 2% 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

6 citing papers in PubMed, 32 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

8 authors at 6 institutions in 3 countries.

Nouf Abdullah AlmujallyDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.ORCID 0000-0003-4405-9912
Turki AljreesCollege of Computer Science and Engineering, University of Hafr Al-Batin, Hafar Al-Batin 39524, Saudi Arabia.ORCID 0000-0002-7473-7115
Oumaima SaidaniDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.ORCID 0000-0001-9520-3174
Muhammad UmerDepartment of Computer Science & Information Technology, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan.ORCID 0000-0002-6015-9326
Zaid Bin FaheemDepartment of Computer Science & Information Technology, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan.ORCID 0000-0003-0355-5119
Nihal AbuzinadahFaculty of Computer Science and Information Technology, King Abdulaziz University, P.O. Box 80200, Jeddah 21589, Saudi Arabia.ORCID 0000-0001-9578-8475
Khaled AlnowaiserDepartment of Computer Engineering, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia.
Imran AshrafDepartment of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.ORCID 0000-0002-8271-6496
Islamia University of Bahawalpur · PKPrincess Nourah bint Abdulrahman University · SAKing Abdulaziz University · SAPrince Sattam Bin Abdulaziz University · SAUniversity of Hafr Al-Batin · SAYeungnam University · KR

Funding

Princess Nourah bint Abdulrahman University Researchers Supporting Project PNURSP2023R410
6 · The paper itself

Abstract

With technological advancements, smart health monitoring systems are gaining growing importance and popularity. Today, business trends are changing from physical infrastructure to online services. With the restrictions imposed during COVID-19, medical services have been changed. The concepts of smart homes, smart appliances, and smart medical systems have gained popularity. The Internet of Things (IoT) has revolutionized communication and data collection by incorporating smart sensors for data collection from diverse sources. In addition, it utilizes artificial intelligence (AI) approaches to control a large volume of data for better use, storing, managing, and making decisions. In this research, a health monitoring system based on AI and IoT is designed to deal with the data of heart patients. The system monitors the heart patient's activities, which helps to inform patients about their health status. Moreover, the system can perform disease classification using machine learning models. Experimental results reveal that the proposed system can perform real-time monitoring of patients and classify diseases with higher accuracy.

Indexed as

COVID-19Heart FailureInternet of ThingsArtificial IntelligenceHumansInternetdeep learningheart diseaseIoTpatient mortality predictionsmart healthcare

Identifiers

PMID37430494
PMCPMC10221603
OpenAlexW4375949972

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.