Designing Algorithm for Malaria Diagnosis using Fuzzy Logic for Treatment (AMDFLT) in Ghana

Duodu, Quashie; Panford, Joseph Kobina; Hayfron-Acquah, James Ben

doi:10.5120/16102-5353

Cited by 8 publications

(5 citation statements)

References 2 publications

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“…Duodu, [28] 2014 Ghana An algorithm for malaria diagnosis and treatment using fuzzy logic was designed and simulated using MATLAB 7. Bojang, [30] 2000 Gambian Symptoms which contributed to the malaria: feels hot, absent of rash and cough, vomiting, reduced feeding, sleeping, and shivering 88% sensitivity and 62% specificity; compared with the pediatrician…”

Section: Major Findings/recommendationsmentioning

confidence: 99%

Development and validation of an online tool for assessment of health care providers’ management of suspected malaria in an area, where transmission has been interrupted

Azizi

Majdzadeh

Ahmadi

et al. 2022

Malar J

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Background The alertness and practice of health care providers (HCPs) in the correct management of suspected malaria (CMSM) (vigilance) is a central component of malaria surveillance following elimination, and it must be established before malaria elimination certification can be granted. This study was designed to develop and validate a rapid tool, Simulated Malaria Online Tool (SMOT), to evaluate HCPs’ practice in relation to the CMSM. Methods The study was conducted in East Azerbaijan Province, Islamic Republic of Iran, where no malaria transmission has been reported since 2005. An online tool presenting a suspected malaria case for detection of HCPs’ failures in recognition, diagnosis, treatment and reporting was developed based on literature review and expert opinion. A total of 360 HCPs were allocated to two groups. In one group their performance was tested by simulated patient (SP) methodology as gold standard, and one month later by the online tool to allow assessment of its sensitivity. In the other group, they were tested only by the online tool to allow assessment of any possible bias incurred by the exposure to SPs before the tool. Results The sensitivity of the tool was (98.7%; CI 93.6–99.3). The overall agreement and kappa statistics were 96.6% and 85.6%, respectively. In the group tested by both methods, the failure proportion by SP was 86.1% (CI 80.1–90.8) and by tool 87.2% (CI 81.4–91.7). In the other group, the tool found 85.6% (CI 79.5–90.3) failures. There were no significant differences in detecting failures within or between the groups. Conclusion The SMOT tool not only showed high validity for detecting HCPs’ failures in relation to CMSM, but it had high rates of agreement with the real-world situation, where malaria transmission has been interrupted. The tool can be used by program managers to evaluate HCPs’ performance and identify sub-groups, whose malaria vigilance should be strengthened. It could also contribute to the evidence base for certification of malaria elimination, and to strengthening prevention of re-establishment of malaria transmission.

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Section: Major Findings/recommendationsmentioning

confidence: 99%

Development and validation of an online tool for assessment of health care providers’ management of suspected malaria in an area, where transmission has been interrupted

Azizi

Majdzadeh

Ahmadi

et al. 2022

Malar J

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“…Different works have been carried out in the medical area using type-1 and interval type-2 fuzzy systems (IT2FS) [28][29][30][31][32][33], which we will briefly describe next.…”

Section: Related Workmentioning

confidence: 99%

Optimal Design of Interval Type-2 Fuzzy Heart Rate Level Classification Systems Using the Bird Swarm Algorithm

et al. 2018

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In this paper, the optimal designs of type-1 and interval type-2 fuzzy systems for the classification of the heart rate level are presented. The contribution of this work is a proposed approach for achieving the optimal design of interval type-2 fuzzy systems for the classification of the heart rate in patients. The fuzzy rule base was designed based on the knowledge of experts. Optimization of the membership functions of the fuzzy systems is done in order to improve the classification rate and provide a more accurate diagnosis, and for this goal the Bird Swarm Algorithm was used. Two different type-1 fuzzy systems are designed and optimized, the first one with trapezoidal membership functions and the second with Gaussian membership functions. Once the best type-1 fuzzy systems have been obtained, these are considered as a basis for designing the interval type-2 fuzzy systems, where the footprint of uncertainty was optimized to find the optimal representation of uncertainty. After performing different tests with patients and comparing the classification rate of each fuzzy system, it is concluded that fuzzy systems with Gaussian membership functions provide a better classification than those designed with trapezoidal membership functions. Additionally, tests were performed with the Crow Search Algorithm to carry out a performance comparison, with Bird Swarm Algorithm being the one with the best results.

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“…The Centre-of-Gravity (CoG) Defuzzification method was used. This is because CoG Defuzzification method is simple and requires less computation effort compared to MOM, MAX, HD and CoS [8]. …”

Section: Impementationmentioning

confidence: 99%

Assessing Lecturers' Performance using Fuzzy Logic

Abdulrahman¹,

Shamsu-Deen²,

Abaidoo³

2017

IJCA

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Assessing lecturers is a routine work conducted at various universities to ascertain the academic performance of the lecturers. In literature, various methods and variables are being employed to do the evaluation. The objective of this research was to employ fuzzy logic in assessment of lecturers as against the traditional statistical methods. Four input variables, namely lecturer delivery, punctuality, interaction with students and assignment were used which produces a single output-Result, with its linguistic terms as Excellent, Fair, Good or Poor. The result shows that Fuzzy logic can be a simpler way of evaluating lecturers.

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Designing Algorithm for Malaria Diagnosis using Fuzzy Logic for Treatment (AMDFLT) in Ghana

Cited by 8 publications

References 2 publications

Development and validation of an online tool for assessment of health care providers’ management of suspected malaria in an area, where transmission has been interrupted

Development and validation of an online tool for assessment of health care providers’ management of suspected malaria in an area, where transmission has been interrupted

Optimal Design of Interval Type-2 Fuzzy Heart Rate Level Classification Systems Using the Bird Swarm Algorithm

Assessing Lecturers' Performance using Fuzzy Logic

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