Software for Occupational Health and Safety Risk Analysis Based on a Fuzzy Model

Stefanović, Miladin; Tadić, Danijela; Djapan, Marko; Mačužić, Ivan

doi:10.1080/10803548.2012.11076923

Cited by 7 publications

(2 citation statements)

References 24 publications

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“…Recently, several fuzzy system free and open source software were produced, through which simulations fuzzy logic can be performed quickly [17]. In this work the evaluations were performed with Fuzzy-Calc, and the MATLAB package, the first an app was used calculate fuzzy indicators with the objective to obtain a synthetic performance value for the study variables, and MATLAB fuzzy logic toolbox was used for comparative study between FNA and ultrasound.…”

Section: Discussionmentioning

confidence: 99%

Use of Fuzzy Logic in the Classification of Thyroid Nodules Detected by Ultrasonography

Andrade

Oliveira²,

Oliveira³

et al. 2022

Preprint

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Objective Employ fuzzy logic to auxiliary in diagnosis and malignancy grade of thyroid nodules by ultrasound. Methods A cross-sectional study evaluating 75 exams results from patients with a thyroid nodule. The following ultrasound findings were evaluated employing a quantitative score: not suspicious, not very suspicious, moderately suspicious, and highly suspicious. The echographic features evaluated for suspicion of malignancy were based on the following nodule components: composition, echogenicity, shape, margin, and echogenic foci, graded using the Thyroid Imaging Data and Reporting System by the American College of Radiology. By combining ultrasound scoring and the Bethesda System for Reporting Thyroid Cytopathology using fuzzy logic, a classification for thyroid nodules was constructed. Results Hypoechogenicity and microcalcifications were the findings that showed the best interaction with malignancy on ultrasound, while shape and margin showed the smallest estimation errors when compared with composition. A classification for thyroid nodules was suggested based on the 95% confidence interval of hypoechogenicity and microcalcifications: not suspicious (< 24.6); not very suspicious (24.6–48.0); moderate (48.1–64.5); moderately suspicious (64.6–77.0); highly suspicious (77.1–92.7); and malignant (> 92.7). Conclusion By fuzzy logic, a classification for thyroid nodules diagnosed by ultrasound supported by echogenicity and nodular microcalcifications was constructed with a simple practical application.

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Section: Discussionmentioning

confidence: 99%

Use of Fuzzy Logic in the Classification of Thyroid Nodules Detected by Ultrasonography

Andrade

Oliveira²,

Oliveira³

et al. 2022

Preprint

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show abstract

“…Factor analysis has also been used for the assessment of workplace violence towards healthcare staff in public hospitals in Turkey [32]. In addition, a fuzzy logic model for OSH risk assessment has been proposed in [33] and a fuzzy cognitive map approach for the impact assessment of processes on the OSH management system's effectiveness has been used in [34]. Ambulatory monitoring devices, such as wearable and environmental sensors, have been combined with ML algorithms for a better understanding of stress evolution in healthcare workers [35].…”

Section: Imentioning

confidence: 99%

Utilization of Machine Learning in Supporting Occupational Safety and Health Decisions in Hospital Workplace

Koklonis

Sarafidis

Vastardi

et al. 2021

Eng. Technol. Appl. Sci. Res.

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The prediction of possible future incidents or accidents and the efficiency assessment of the Occupational Safety and Health (OSH) interventions are essential for the effective protection of healthcare workers, as the occupational risks in their workplace are multiple and diverse. Machine learning algorithms have been utilized for classifying post-incident and post-accident data into the following 5 classes of events: Needlestick/Cut, Falling, Incident, Accident, and Safety. 476 event reports from Metaxa Cancer Hospital (Greece), during 2014-2019, were used to train the machine learning models. The developed models showed high predictive performance, with area under the curve range 0.950-0.990 and average accuracy of 93% on the 10-fold cross set, compared to the safety engineer’s study reports. The proposed DSS model can contribute to the prediction of incidents or accidents and efficiency evaluation of OSH interventions.

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The Quick Exposure Check (QEC) Model Proposal Based on Fuzzy Logic for Work-Related Musculoskeletal Risk Assessment

Kose

Karabayır

Çevikcan

2019

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

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Software for Occupational Health and Safety Risk Analysis Based on a Fuzzy Model

Cited by 7 publications

References 24 publications

Use of Fuzzy Logic in the Classification of Thyroid Nodules Detected by Ultrasonography

Use of Fuzzy Logic in the Classification of Thyroid Nodules Detected by Ultrasonography

Utilization of Machine Learning in Supporting Occupational Safety and Health Decisions in Hospital Workplace

The Quick Exposure Check (QEC) Model Proposal Based on Fuzzy Logic for Work-Related Musculoskeletal Risk Assessment

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