Tracking and preventing diseases with artificial intelligence / Mayuri Mehta, Philippe Fournier-Viger, Maulika Patel, Jerry Chun-Wei Lin, editors.
2022
R859.7.A78 T73 2022
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Details
Title
Tracking and preventing diseases with artificial intelligence / Mayuri Mehta, Philippe Fournier-Viger, Maulika Patel, Jerry Chun-Wei Lin, editors.
ISBN
9783030767327 (electronic bk.)
3030767329 (electronic bk.)
9783030767310
3030767310
3030767329 (electronic bk.)
9783030767310
3030767310
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (266 pages) : illustrations (some color)
Item Number
10.1007/978-3-030-76732-7 doi
Call Number
R859.7.A78 T73 2022
Dewey Decimal Classification
610.28563
Summary
This book presents an overview of how machine learning and data mining techniques are used for tracking and preventing diseases. It covers several aspects such as stress level identification of a person from his/her speech, automatic diagnosis of disease from X-ray images, intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells, information retrieval from electronic medical record using named entity recognition approaches, and prediction of drug-target interactions. The book is suitable for computer scientists having a bachelor degree in computer science. The book is an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care. Researchers working in the multidisciplinary areas use this book to discover the current developments. Besides its use in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases. Medical institutions use this book as reference material and give tutorials to medical experts on how the advanced AI and ML techniques contribute to the diagnosis and prediction of the diseases.
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Access limited to authorized users.
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text file
PDF
Source of Description
Description based on print version record.
Online resource; title from PDF title page (SpringerLink, viewed July 29, 2021).
Online resource; title from PDF title page (SpringerLink, viewed July 29, 2021).
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Series
Intelligent systems reference library ; v. 206.
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Table of Contents
Stress Identification from Speech using Clustering techniques
Comparative Study and Detection of COVID-19 and Related Viral Pneumonia using a Fine-tuned Deep Transfer Learning
Predicting Glaucoma Diagnosis using AI
Diagnosis and Analysis of Tuberculosis Disease using Simple Neural Network and Deep Learning Approach for Chest X-ray Images
Adaptive Machine Learning Algorithm and Analytics of Big Genomic Data for Gene Prediction.
Comparative Study and Detection of COVID-19 and Related Viral Pneumonia using a Fine-tuned Deep Transfer Learning
Predicting Glaucoma Diagnosis using AI
Diagnosis and Analysis of Tuberculosis Disease using Simple Neural Network and Deep Learning Approach for Chest X-ray Images
Adaptive Machine Learning Algorithm and Analytics of Big Genomic Data for Gene Prediction.