Literature DB >> 16521432

[Algorithms of artificial neural networks--practical application in medical science].

Bogusław Stefaniak1, Witold Cholewiński, Anna Tarkowska.   

Abstract

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer applications of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. This paper presents practical aspects of scientific application of ANN in medicine using widely available algorithms. Several main steps of analysis with ANN were discussed starting from material selection and dividing it into groups, to the quality assessment of obtained results at the end. The most frequent, typical reasons for errors as well as the comparison of ANN method to the modeling by regression analysis were also described.

Mesh:

Year:  2005        PMID: 16521432

Source DB:  PubMed          Journal:  Pol Merkur Lekarski        ISSN: 1426-9686


  3 in total

1.  Opening the black box of neural networks: methods for interpreting neural network models in clinical applications.

Authors:  Zhongheng Zhang; Marcus W Beck; David A Winkler; Bin Huang; Wilbert Sibanda; Hemant Goyal
Journal:  Ann Transl Med       Date:  2018-06

2.  Binary logistic regression modeling with TensorFlow™.

Authors:  Zhongheng Zhang; Lei Mo; Chen Huang; Ping Xu
Journal:  Ann Transl Med       Date:  2019-10

3.  Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study.

Authors:  Antônio Carlos da Silva Júnior; Michele Jorge da Silva; Cosme Damião Cruz; Isabela de Castro Sant'Anna; Gabi Nunes Silva; Moysés Nascimento; Camila Ferreira Azevedo
Journal:  PLoS One       Date:  2021-11-29       Impact factor: 3.240

  3 in total

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