ArticleJournal of medical systems2012
Determination of women iron deficiency anemia using neural networks.
Article in Journal of medical systems, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 24 citations in OpenAlex.
- Artificial Intelligence in Patient Blood Management: A Systematic Review of Predictive, Diagnostic, and Decision Support Applications.Journal of clinical medicine · 2025Review
- A Novel Expert System for Diagnosis of Iron Deficiency Anemia.Computational and mathematical methods in medicine · 2022Article
- Differential Diagnosis of Iron-Deficiency Anemia from β-Thalassemia Trait Using an Intelligent Model in Comparison with Discriminant Indexes.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2019Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
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