An Extended Approach to Predict Retinopathy in Diabetic Patients Using the Genetic Algorithm and Fuzzy C-Means.
The present study is developed a new approach using a computer diagnostic method to diagnosing diabetic diseases with the use of fluorescein images. In doing so, this study presented the growth region algorithm for the aim of diagnosing diabetes, considering the angiography images of the patients' e...
| Publicado en: | BioMed Research International pp. 1 - 14 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
6/28/2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151120609&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151120609 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 6/28/2021 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 151120609 151120609 151120609 10.1155/2021/5597222 151120609 ppf: 1 ppct: 13 formats: fmt: @attributes: type: P tig: atl: An Extended Approach to Predict Retinopathy in Diabetic Patients Using the Genetic Algorithm and Fuzzy C-Means. aug: au: Ghoushchi, Saeid Jafarzadeh Ranjbarzadeh, Ramin Dadkhah, Amir Hussein Pourasad, Yaghoub Bendechache, Malika affil: Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran sug: subj: Diabetic Retinopathy Diagnosis Genetic Algorithms Diabetic Retinopathy Risk Factors Diagnosis, Computer Assisted Prediction Models Risk Assessment Tomography, Optical Coherence Methods Angiography Human Descriptive Statistics Diabetes Mellitus Complications Sensitivity and Specificity Diabetes Mellitus Diagnosis Diabetic Patients ab: The present study is developed a new approach using a computer diagnostic method to diagnosing diabetic diseases with the use of fluorescein images. In doing so, this study presented the growth region algorithm for the aim of diagnosing diabetes, considering the angiography images of the patients' eyes. In addition, this study integrated two methods, including fuzzy C-means (FCM) and genetic algorithm (GA) to predict the retinopathy in diabetic patients from angiography images. The developed algorithm was applied to a total of 224 images of patients' retinopathy eyes. As clearly confirmed by the obtained results, the GA-FCM method outperformed the hand method regarding the selection of initial points. The proposed method showed 0.78 sensitivity. The comparison of the fuzzy fitness function in GA with other techniques revealed that the approach introduced in this study is more applicable to the Jaccard index since it could offer the lowest Jaccard distance and, at the same time, the highest Jaccard values. The results of the analysis demonstrated that the proposed method was efficient and effective to predict the retinopathy in diabetic patients from angiography images. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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