Author Type

Graduate Student

Date of Award

2014

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Agarwal, Ankur

Abstract

Wellness and healthy life are the most common concerns for an individual to lead a happy life. A web-based approach known as Wellness Scoring is being developed taking into people’s concerns for their health issues. In this approach, four different classifiers are being investigated to predict the wellness. In this thesis, we investigated four different classifiers (a probabilistic graphical model, simple probabilistic classifier, probabilistic statistical classification and an artificial neural network) to predict the wellness outcome. An approach to calculate wellness score is also addressed. All these classifiers are trained on real data, hence giving more accurate results. With this solution, there is a better way of keeping track of an individuals’ health. In this thesis, we present the design and development of such a system and evaluate the performance of the classifiers and design considerations to maximize the end user experience with the application. A user experience model capable of predicting the wellness score for a given set of risk factors is developed.

Extent

73 p.

Comments

Includes bibliography.|Thesis (M.S.)--Florida Atlantic University, 2014.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.

Identifier

FA00004321

Format

pdf

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