Logistic regression and artificial neural network classification models: a methodology review

Logistic regression and artificial neural networks are the models of choice in many medical data classification tasks. In this review, we summarize the differences and similarities of these models from a technical point of view, and compare them with other machine learning algorithms. We provide considerations useful for critically assessing the quality of the models and the results based on these models. Finally, we summarize our findings on how quality criteria for logistic regression and artificial neural network models are met in a sample of papers from the medical literature.

• Publication year

  2002

• Venue

  Journal of Biomedical Informatics

• Publication date

  2002-10-01

• Fields of study

  Medicine, Computer Science, Psychology

• Identifiers
  DOI 10.1016/S1532-0464(03)00034-0PMID 12968784
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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