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2. Linguistic Parameters of Spontaneous Speech for Identifying Mild Cognitive Impairment and Alzheimer Disease.

Author

Vincze, Veronika, Szabó, Martina Katalin, Hoffmann, Ildikó, Tóth, László, Pákáski, Magdolna, Kálmán, János, and Gosztolya, Gábor

Subjects
MILD cognitive impairment, ALZHEIMER'S disease, SPEECH, DATA recorders & recording, PRAGMATICS, MACHINE learning
Abstract

In this article, we seek to automatically identify Hungarian patients suffering from mild cognitive impairment (MCI) or mild Alzheimer disease (mAD) based on their speech transcripts, focusing only on linguistic features. In addition to the features examined in our earlier study, we introduce syntactic, semantic, and pragmatic features of spontaneous speech that might affect the detection of dementia. In order to ascertain the most useful features for distinguishing healthy controls, MCI patients, and mAD patients, we carry out a statistical analysis of the data and investigate the significance level of the extracted features among various speaker group pairs and for various speaking tasks. In the second part of the article, we use this rich feature set as a basis for an effective discrimination among the three speaker groups. In our machine learning experiments, we analyze the efficacy of each feature group separately. Our model that uses all the features achieves competitive scores, either with or without demographic information (3-class accuracy values: 68%–70%, 2-class accuracy values: 77.3%–80%). We also analyze how different data recording scenarios affect linguistic features and how they can be productively used when distinguishing MCI patients from healthy controls. [ABSTRACT FROM AUTHOR]

Published
2022
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3. Smart Medical Imaging for Diagnosis and Treatment Planning

Author

Nilanjan Dey, Bitan Misra, Sayan Chakraborty, Nilanjan Dey, Bitan Misra, and Sayan Chakraborty

Subjects
Artificial intelligence
Abstract

This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques. It shows how smart health technologies leverage artificial intelligence (AI) and big data analytics to provide more accurate and efficient diagnosis and treatment planning. In search for innovative and novel methods and techniques for health technologies and medical data processing, the book • Discusses applications of Artificial Intelligence, Data Science, Machine Learning, Deep Learning, the Internet of Things, Big Data, Cloud Computing;• Includes use of electronic patient records in healthcare, analysis of big data in medical diagnosis, reliability, and challenges of EPR and EHR in smart healthcare;• Explores evolving techniques for smart healthcare, its application in medical imaging and prediction in the fields of treatment planning;• Provides recent studies in AI-driven healthcare technologies and medical imaging to outline insight into smart healthcare technologies;• Discusses the role of big data in smart healthcare, computing techniques for healthcare for medical diagnosis and treatment planning;• Encompasses the ethical and legal challenges of using smart healthcare and medical data.This book serves as a valuable reference for researchers working on smart health technologies. Researchers of medical imaging, artificial intelligence, and data science along with healthcare domain will find it a great resource as well.

Published
2024

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