Evidence map›Paper›PMID 33147715›Full record

ArticleInternational journal of environmental research and public health2020

Prototype Development of an Expert System of Computerized Clinical Guidelines for COVID-19 Diagnosis and Management in Saudi Arabia.

Haneen Reda Banjar, Heba Alkhatabi, Nofe Alganmi, Ghaidaa Ibraheem Almouhana

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. An IoT Framework for Screening of COVID-19 Using Real-Time Data from Wearable Sensors.International journal of environmental research and public health · 2021
    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

4 authors at 1 institution in 1 country.

Haneen Reda BanjarComputer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 80200, Saudi Arabia.ORCID 0000-0003-4475-4878
Heba AlkhatabiDepartment of Medical Laboratory Technology, Faculty of Applied Medical Science, King Abdulaziz University, Jeddah 80200, Saudi Arabia.
Nofe AlganmiComputer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 80200, Saudi Arabia.
Ghaidaa Ibraheem AlmouhanaComputer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 80200, Saudi Arabia.
King Abdulaziz University · SA

Funding

King Abdulaziz University DF-388-165-1441
6 · The paper itself

Abstract

The increasing number of COVID-19 patients has increased health care professionals' workloads, making the management of dynamic patient information in a timely and comprehensive manner difficult and sometimes impossible. Compounding this problem is a lack of health care professionals and trained medical staff to handle the increased number of patients. Although Saudi Arabia has recently improved the quality of its health services, there is still no suitable intelligent system that can help health practitioners follow the clinical guidelines and automated risk assessment and treatment plan remotely, which would allow for the effective follow-up of patients of COVID-19. The proposed system includes five sub-systems: an information management system, a knowledge-based expert system, adaptive learning, a notification and follow-up system, and a mobile tracker system. This study shows that, to control epidemics, there is a method to overcome the shortage of specialists in the management of infections in Saudi Arabia, both today and in the future. The availability of computerized clinical guidance and an up-to-date knowledge base play a role in Saudi health organizations, which may not have to constantly train their physician staff and may no longer have to rely on international experts, since the expert system can offer clinicians all the information necessary to treat their patients.

Indexed as

Expert SystemsPractice Guidelines as TopicBetacoronavirusClinical Laboratory TechniquesCoronavirus InfectionsCOVID-19COVID-19 TestingHumansPandemicsPneumonia, ViralSARS-CoV-2Saudi Arabiaclinical guidelineCOVID-19 managementexpert systemmobile track and evolution of expert system

Identifiers

PMID33147715
PMCPMC7662618
OpenAlexW3096113106

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.