Design of meta-semantic analysis for automatic detection of Alzheimer's disease Öffentlichkeit

Abstract

Nowadays, manual diagnosis of early stages of neurodegenerative disorders such as Alzheimer’s disease (AD) has been a challenge. While current neuropsychological examinations often fail to provide satisfactory result in detecting Mild Cognitive Impairment (MC) and linguistic ability has shown to be a good indication of symptoms of AD, in this thesis I examine the semantic linguistic features resulting from verbal utterances of potential patients to distinguish healthy people and people with the disease. For this purpose, I perform statistical and machine learning analysis on a specific language transcript dataset, consisting of 50 healthy people and 50 probable MCIs. Experimental and statistical evaluations suggest that certain patterns and semantic features are effective in helping the clinical diagnosis of MCI. 

Table of Contents

1 Introduction                                                             1

1.1 Manual Diagnosis of AD . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1

1.2 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

1.3 Why Meta-Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3 Motivation and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

2 Background                                                              6

2.1 Significance of Linguistic Ability in Detecting AD . . . . . . . . . . .  6

2.2 Picture Description and Linguistic Ability . . . . . . . . . . . . . . . .  7

3 Approach                                                                8

3.1 Dataset and Tools. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  8

3.2 Annotation Guideline. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4 Analysis                                                                  42

4.1 Observational . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  42

4.2 Statistical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

                 4.2.1 General Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . .  44

                 4.2.2 Mention Weight . . . . . . . . . . . . . . . . . . . . . . . . . . . .   44

                 4.2.3 Mention Density. . . . . . . . . . . . . . . . . . . . . . . . . . . . .  47

                 4.2.4 Predicate Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . .  48

                 4.2.5 Attribute Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.2.6 Xmod Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  51

4.2.7 Nmod Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

5 Limitations and Future Works                                        54

About this Honors Thesis

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School	Emory College
Department	Computer Science
Degree	B.S.
Submission	Honors Thesis
Language	English
Research Field	Artificial Intelligence Language, Linguistics Computer Science
Stichwort	brain health Alzheimer's Disease natural language processing
Committee Chair / Thesis Advisor	Jinho D. Choi, Emory University
Committee Members	Juliette Stapanian Apkarian, Emory University James Nagy, Emory University

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