A fuzzy rule-based expert system for diagnosing cystic fibrosis

Hassanzad, Maryam; Orooji, Azam; Valinejadi, Ali; Velayati, A A

doi:10.19082/5974

Cited by 19 publications

(19 citation statements)

References 22 publications

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“…In spite of the emphasis in the clinical guidelines on the early detection of cardiac arrest and immediate intervention by the CPR team [1,13,14], unfortunately, there have been very few studies conducted on the arrival time of physician and resuscitation team and its association with the outcome of resuscitation. Therefore, this study was conducted with the objective of evaluating the arrival time of physician and resuscitation team at Imam Reza Hospital of Kermanshah in Iran during 2018.…”

Section: Introductionmentioning

confidence: 99%

Assessing the effect of arrival time of physician and cardiopulmonary resuscitation (CPR) team on the outcome of CPR

Ezzati

Mohammadi

Karimpour

et al. 2020

IMAS

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Introduction Negligence of proper time and poor performance of resuscitation team can lead to more mortality and negative consequences of cardiac arrest, as well as less survival. This study was conducted with objective of determining the arrival time of physician and resuscitation team to survive the victims of cardiopulmonary arrest. Materials and methods In this prospective and descriptive-analytic study, the resuscitation performance and the arrival time of resuscitation team in 143 inpatients who had been diagnosed with witnessed cardiopulmonary arrest were examined using a researcher-made checklist. Data analysis was performed using parametric and non-parametric statistical tests and SPSS. Results Initial survival rate was 26.6%. In general, the mean time of physician’s presence after the code announcement in minutes and seconds was 02:31 ± 01:22. It was also 02:24 ± 01:15 in successful cases and 02:34 ± 01:25 in unsuccessful cases. Independent t-test did not show a significant difference between the physician’s presence time and the rate of initial successful resuscitation (p = 0.504). The time of first shock after observing ventricular fibrillation/tachycardia (in minutes and seconds) was 01:30 ± 00:47. According to independent t-test, the aforementioned time was less than the mean time (02:31 ± 01:22) of physician’s presence (p < 0.001). Conclusions In this study, the initial survival rate in comparison to other regions in the country was almost more favorable and it was similar to global norms. In this study, the starting time of resuscitation was within the acceptable range. There was no relationship between the presence of physician and the initial survival rate of patients, as well as the use of defibrillator (by physician compared to other team members) and intubation with the initial survival rate. This could indicate the adequate performance of resuscitation team in the absence of physician on the condition of having sufficient knowledge and skill.

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Section: Introductionmentioning

confidence: 99%

Assessing the effect of arrival time of physician and cardiopulmonary resuscitation (CPR) team on the outcome of CPR

Ezzati

Mohammadi

Karimpour

et al. 2020

IMAS

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“…Regarding the diseases under study, an important variability in the number of targeted diseases was identified. The most individually studied diseases were thalassemia [20,28,29,47], Down syndrome [21,30,34], cystic fibrosis [46,48,52], Marfan syndrome [25,27] and Huntington disease [19,33].…”

Section: Publication Targetmentioning

confidence: 99%

“…The protocol to evaluate and validate the developed models was highly study-dependent and is detailed in the next subsections. The following characteristics were considered: Hybrid (7 studies) Yes [27,[73][74][75][76]78] No [25] Data driven (1 study) Yes [72] Fluids (12 studies) Hybrid (2 studies) Yes [28,29] Data driven (10 studies) Yes [20,23,24,31,36,42,47,48,56,60] Images (16 studies) Hybrid (2 studies) Yes [41,45] Data driven (14 studies) Yes [19, 21, 22, 30, 33-35, 43, 44, 49, 51, 57, 59, 62] Questionnaires (3 studies) Data driven (3 studies) Yes [52,53,58] Family history and combined material (8 studies) Knowledge-based (5 studies) No [26,32,38,46,50] Hybrid (2 studies) Yes [37,39] Data driven (1 study) Yes [40] References are listed in column "articles" according to the type of material considered and the model used (presence/absence of prior knowledge and of machine learning). The number of studies according to material and knowledge is given in parentheses Fig.…”

Section: Evaluation and Validationmentioning

confidence: 99%

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Diagnosis support systems for rare diseases: a scoping review

Faviez

Chen

Garcelon

et al. 2020

Orphanet J Rare Dis

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Introduction: Rare diseases affect approximately 350 million people worldwide. Delayed diagnosis is frequent due to lack of knowledge of most clinicians and a small number of expert centers. Consequently, computerized diagnosis support systems have been developed to address these issues, with many relying on rare disease expertise and taking advantage of the increasing volume of generated and accessible health-related data. Our objective is to perform a review of all initiatives aiming to support the diagnosis of rare diseases. Methods: A scoping review was conducted based on methods proposed by Arksey and O'Malley. A charting form for relevant study analysis was developed and used to categorize data. Results: Sixty-eight studies were retained at the end of the charting process. Diagnosis targets varied from 1 rare disease to all rare diseases. Material used for diagnosis support consisted mostly of phenotype concepts, images or fluids. Fifty-seven percent of the studies used expert knowledge. Two-thirds of the studies relied on machine learning algorithms, and one-third used simple similarities. Manual algorithms were encountered as well. Most of the studies presented satisfying performance of evaluation by comparison with references or with external validation. Fourteen studies provided online tools, most of which aimed to support the diagnosis of all rare diseases by considering queries based on phenotype concepts. Conclusion: Numerous solutions relying on different materials and use of various methodologies are emerging with satisfying preliminary results. However, the variability of approaches and evaluation processes complicates the comparison of results. Efforts should be made to adequately validate these tools and guarantee reproducibility and explicability.

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“…Cystic fibrosis (CF) patients often have respiratory tract infections and bacterial colonization that require antibiotic therapy. Pseudomonas infection and a number of previous admissions have shown to be the major predictors of mortality in CF (2)(3)(4). The most common organisms causing respiratory infections in CF patients are pseudomonas aeruginosa, staphylococcus aureus, and stenotrophomonas maltophilia (5).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Fraction of Exhaled Nitric Oxide (FeNO) in CF Children and its Association with Sputum Culture

et al. 2019

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Background: Exhaled nitric oxide (FeNO) in cystic fibrosis (CF) patients is reduced when compared with healthy people, and it has now been found that FeNO has a relative association with airway clearance index. Studies have shown the role of some infections in changing the FeNO level; however, the role of respiratory infections in FeNO has not yet been thoroughly studied. Objectives: The objective of this study was to investigate the possibility of FeNO usage to monitor the infections in CF patients. Methods: This cross-sectional case-control study was conducted on CF patients between the age of five to 18 with positive sputum culture, through simple non-random census method. FeNO levels were measured in 30 healthy children and 30 CF children with positive sputum culture. CF patients were treated by antibiotic therapy for two weeks; in the case offending negative sputum culture, the FeNO level was re-measured. FeNO levels were re-evaluated in 13 patients after four weeks. Results: There was no statistical difference between both groups in terms of age and weight. The level of FeNO in CF patients was significantly lower than in healthy children (22.1 ± 10.1 versus 30.0 ± 11.0 in the control group and P = 0.003). In 27 children, two weeks after administration of antibiotic therapy, sputum culture was negative. The mean of FeNO in these patients was 16.4 ± 5.5 at the time of the negative sputum culture, which was significantly lower than FeNO before starting the treatment. (P: 0.003). The mean FeNO was 13.0 ± 7.41 in 13 patients who were re-measured four weeks after starting the treatment. There was no significant difference between FeNO level two weeks after treatment and four weeks after starting treatment (P: 0.292). Patients with pseudomona sputum culture were not significantly different from those with non-pseudomona sputum culture in terms of primary FeNO and FeNO changes after the treatment (P value: 0.084 and 0.094, respectively). Conclusions: However, in our study, FeNO was decreased after administration of antibiotic treatment in CF patients, but according to the sample size and conflicting or similar results in other studies, currently, FeNO levels cannot be used as a way of monitoring the treatment of infection in CF patients.

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A fuzzy rule-based expert system for diagnosing cystic fibrosis

Cited by 19 publications

References 22 publications

Assessing the effect of arrival time of physician and cardiopulmonary resuscitation (CPR) team on the outcome of CPR

Assessing the effect of arrival time of physician and cardiopulmonary resuscitation (CPR) team on the outcome of CPR

Diagnosis support systems for rare diseases: a scoping review

Evaluation of Fraction of Exhaled Nitric Oxide (FeNO) in CF Children and its Association with Sputum Culture

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