NDLI: Performance of neural nets, CART, and Cox models for censored survival data

Content Provider	IEEE Xplore Digital Library
Author	Kates, R.E. Berger, U. Ulm, B.K. Harbeck, N. Graeff, H. Schmitt, M.
Copyright Year	1999
Description	Author affiliation: Inst. fur Med. Stat. und Epidemiologie, Tech. Univ. Munchen, Germany (Kates, R.E.)
Abstract	Illustrates the relative performance of several techniques for nonlinear predictive modeling of simulated censored clinical survival data on the basis of measured risk factors: a neural net approach developed in our group, the CART (classification and regression trees) technique, and the Cox model with (and without) quadratic interactions. Simulated follow-up data is first generated by combining empirical multivariate distributions of clinical factors in breast cancer patients with hypothetical nonlinear risk structures, which are thus "known". The performance of these analysis methods is evaluated by comparing the "known" and predicted scores on training and validation (generalization) samples containing 500 patients each. The neural net has the best performance for a complex risk structure in which three-factor interactions play an important role.
Starting Page	309
Ending Page	312
File Size	326481
Page Count	4
File Format	PDF
ISBN	0780355784
DOI	10.1109/KES.1999.820185
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-08-31
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Predictive models Breast cancer Particle measurements Performance analysis Decision making Medical treatment Diseases Computer networks Artificial neural networks
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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