Evidence map›Paper›PMID 21912973›Full record

ArticleJournal of medical systems2012

Fuzzy rule-based expert system for evaluating level of asthma control.

Maryam Zolnoori, Mohammad Hosain Fazel Zarandi, Mostafa Moin, Mehran Taherian

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Article in Journal of medical systems, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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4 · The record

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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.

Maryam ZolnooriDepartment of Information Technology Management, Tarbiat Modares University, Tehran, Iran. m.zolnoori@gmail.com
Mohammad Hosain Fazel Zarandi
Mostafa Moin
Mehran Taherian

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Asthma control is a final goal of asthma therapy process. Despite outstanding progress in discovering various variables affecting asthma control levels, disregarding some of them by physicians and variables' inherent uncertainty are the major causes of underestimating of asthma control levels and as a result asthma morbidity and mortality. In this paper, we provide an intelligent fuzzy system as a solution for this problem. Inputs of this system are composed of 14 variables organized in five modules of respiratory symptoms severity, bronchial obstruction, asthma instability, current treatment, and quality of life. Output of this system is degree of asthma control defined in the score (0-10). Evaluation of performance of this system by 42 asthmatic patients at asthma, allergy, immunology research center of Emam Khomeini hospital, Tehran, Iran reinforces that the system's results not only correspond with the evaluations of experienced asthma physicians, but represents slight differences in the levels of asthma control between asthmatic patients.

Indexed as

Fuzzy LogicAirway ObstructionAlgorithmsAnti-Asthmatic AgentsAsthmaHumansQuality of Health CareQuality of LifeReproducibility of ResultsSeverity of Illness IndexAnti-Asthmatic Agents

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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.