期刊
JOURNAL OF BIOMEDICAL INFORMATICS
卷 35, 期 5-6, 页码 352-359出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/S1532-0464(03)00034-0
关键词
artificial neural networks; logistic regression; classification; model comparison; model evaluation; medical data analysis
资金
- NLM NIH HHS [R01 LM006538] Funding Source: Medline
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. (C) 2003 Elsevier Science (USA). All rights reserved.
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