Discrimination of β-thalassemia and iron deficiency anemia through extreme learning machine and regularized extreme learning machine based decision support system.
The symptoms of Iron Deficiency Anemia (IDA) and β-thalassemia (β-TT) disease are similar and the distinction between them is time consuming and costly. There are several indices used to differentiate IDA from β-thalassemia disease. Complete Blood Count (CBC) is a rapid, inexpensive and accessible t...
| Publicado en: | Medical Hypotheses Vol. 135; pp. 109611 - 109612 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Elsevier B.V.
Feb2020
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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=141667952&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141667952 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03069877 NZO jtl: Medical Hypotheses issn: 03069877 maglogo: N pubinfo: dt: Feb2020 vid: 135 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 141667952 141667952 NLM32036196 10.1016/j.mehy.2020.109611 NLM32036196 141667952 ppf: 109611 ppct: 1 formats: tig: atl: Discrimination of β-thalassemia and iron deficiency anemia through extreme learning machine and regularized extreme learning machine based decision support system. aug: au: Çil, Betül Ayyıldız, Hakan Tuncer, Taner affil: Firat University, Department of Computer Engineering, 23119 Elazig, Turkey sug: subj: beta-Thalassemia Complications Anemia, Iron Deficiency Diagnosis beta-Thalassemia Diagnosis Extreme Learning Machines Decision Support Systems, Clinical Diagnosis, Differential Male Hemoglobins Child Iron Female Child: 6-12 years Male Female ab: The symptoms of Iron Deficiency Anemia (IDA) and β-thalassemia (β-TT) disease are similar and the distinction between them is time consuming and costly. There are several indices used to differentiate IDA from β-thalassemia disease. Complete Blood Count (CBC) is a rapid, inexpensive and accessible test for the diagnosis of anemia and is used as a primary test. However, since CBC cannot fully distinguish between IDA and β-thalassemia, more advanced testing is required. These tests are not available in small centers and are performed on higher-cost devices. Moreover, it is important to differentiate between anemia and β-thalassemia medically for two reasons (IDA). First, if a patient with β-Thalassemia is diagnosed with IDA, the patient is given unnecessary iron supplementation as a result of the treatment, which is recommended by the doctor. Secondly, when the patient with β-thalassemia is diagnosed with IDA, children will have β-thalassemia patients in marriages. A decision support system to distinguish between β-Thalassemia and IDA has been developed. Logistic Regression, K-Nearest Neighbours, Support Vector Machine, Extreme Learning Machine and Regularized Extreme Learning Machine classification algorithms were used in the proposed system. Classification performance was evaluated with Accuracy, sensitivity, f-measure, Specificty parameters using Hemoglobin, RBC, HCT, MCV, MCH, MCHC and RDW parameters obtained from 342 patients. 96.30% accuracy for female, 94.37% for male, and 95.59% in co-evaluation of male and female patients were obtained. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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