Evidence map›Paper›PMID 36850457›Full record

ArticleSensors (Basel, Switzerland)2023

Intelligent Emotion and Sensory Remote Prioritisation for Patients with Multiple Chronic Diseases.

A H Alamoodi, O S Albahri, A A Zaidan, H A Alsattar, B B Zaidan, A S Albahri, Amelia Ritahani Ismail, Gang Kou, Laith Alzubaidi, Mohammed Talal

Abstract read
PubMed Full text at PMC Publisher
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 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

10 authors.

A H AlamoodiFaculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI), Tanjong Malim 35900, Perak, Malaysia.ORCID 0000-0003-4393-5570
O S AlbahriComputer Techniques Engineering Department, Mazaya University College, Nassiriya 12733, Thi-Qar, Iraq.ORCID 0000-0002-7844-3990
A A ZaidanSP Jain School of Global Management, Lidcombe, Sydney, NSW 2141, Australia.
H A AlsattarDepartment of Business Administration, College of Administrative Science, The University of Mashreq, Baghdad 10021, Iraq.
B B ZaidanFuture Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan.
A S AlbahriIraqi Commission for Computers and Informatics (ICCI), Baghdad 10022, Iraq.ORCID 0000-0003-3335-457X
Amelia Ritahani IsmailDepartment of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia.
Gang KouSchool of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, No. 555, Liutai Road, Wenjiang District, Chengdu 611130, China.ORCID 0000-0002-9220-8647
Laith AlzubaidiSchool of Mechanical, Medical, and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia.ORCID 0000-0002-7296-5413
Mohammed TalalDepartment of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat 86400, Malaysia.

Funding

Australian Research Council IC190100020
6 · The paper itself

Abstract

An intelligent remote prioritization for patients with high-risk multiple chronic diseases is proposed in this research, based on emotion and sensory measurements and multi-criteria decision making. The methodology comprises two phases: (1) a case study is discussed through the adoption of a multi-criteria decision matrix for high-risk level patients; (2) the technique for reorganizing opinion order to interval levels (TROOIL) is modified by combining it with an extended fuzzy-weighted zero-inconsistency (FWZIC) method over fractional orthotriple fuzzy sets to address objective weighting issues associated with the original TROOIL. In the first hierarchy level, chronic heart disease is identified as the most important criterion, followed by emotion-based criteria in the second. The third hierarchy level shows that Peaks is identified as the most important sensor-based criterion and chest pain as the most important emotion criterion. Low blood pressure disease is identified as the most important criterion for patient prioritization, with the most severe cases being prioritized. The results are evaluated using systematic ranking and sensitivity analysis.

Indexed as

Heart DiseasesHypotensionEmotionsHumansIntelligencePatientsemotion criteriamulti-chronic diseasesmulti-criteria decision makingpatients prioritisationsensor criteria

Identifiers

PMID36850457
PMCPMC9959399

What OpenQuestion holds

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Registered trials

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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.