Author Type

Graduate Student

Date of Award

2011

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Abstract

The efforts addressed in this thesis refer to applying nonlinear risk predictive techniques based on logistic regression to medical diagnostic test data. This study is motivated and pursued to address the following: 1. To extend logistic regression model of biostatistics to medical informatics 2. Computational preemptive and predictive testing to determine the probability of occurrence (p) of an event by fitting a data set to a (logit function) logistic curve: Finding upper and lower bounds on p based on stochastical considerations 3. Using the model developed on available (clinical) data to illustrate the bounds-limited performance of the prediction. Relevant analytical methods, computational efforts and simulated results are presented. Using the results compiled, the risk evaluation in medical diagnostics is discussed with real-world examples. Conclusions are enumerated and inferences are made with directions for future studies.

Extent

xi, 84 p. : ill. (some col.)

Comments

by Alice Horn Dupont.|Thesis (M.S.C.S.)--Florida Atlantic University, 2011.|Includes bibliography.|Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.|by Alice Horn Dupont.

Identifier

FADT3332187

Format

pdf

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