Literature DB >> 21882005

Determination of women iron deficiency anemia using neural networks.

Ziynet Yılmaz1, M Recep Bozkurt.   

Abstract

Iron deficiency anemia (IDA) is a common type of anemia which most often occurs in young adult women. Detection of Iron deficiency requires blood tests and doctors' decision. Doing so can be costly and difficult especially in undeveloped countries. In this study, we developed an application by using Feedforward Networks (FFN), Cascade Forward Networks (CFN), Distributed Delay Networks (DDN), Time Delay Networks (TDN), Probabilistic Neural Network (PNN), and Learning Vector Quantization (LVQ) networks that can diagnose iron deficiency anemia in women.

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Year:  2011        PMID: 21882005     DOI: 10.1007/s10916-011-9772-4

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  3 in total

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Authors: 
Journal:  World Health Organ Tech Rep Ser       Date:  1968

Review 2.  The prevalence of nutritional anaemia in women in developing countries: a critical review of available information.

Authors:  E Royston
Journal:  World Health Stat Q       Date:  1982

3.  Artificial intelligence models for predicting iron deficiency anemia and iron serum level based on accessible laboratory data.

Authors:  Iman Azarkhish; Mohammad Reza Raoufy; Shahriar Gharibzadeh
Journal:  J Med Syst       Date:  2011-04-19       Impact factor: 4.460

  3 in total
  1 in total

1.  Differential Diagnosis of Iron-Deficiency Anemia from β-Thalassemia Trait Using an Intelligent Model in Comparison with Discriminant Indexes.

Authors:  Leila Kabootarizadeh; Amir Jamshidnezhad; Zahra Koohmareh
Journal:  Acta Inform Med       Date:  2019-06
  1 in total

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