Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education

The present reprint contains all of the articles accepted and published in the Special Issue " Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education" from the MDPI journal Mathematics. This Special Issue aims to develop more efficient and...

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Bibliographic Details
Other Authors: Lacave, Carmen (Editor), Molina, Ana Isabel (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
ECG
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Summary:The present reprint contains all of the articles accepted and published in the Special Issue " Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education" from the MDPI journal Mathematics. This Special Issue aims to develop more efficient and effective approaches to healthcare and education, leveraging the increasing availability of big data and advancements in artificial intelligence. By sharing new methods, applications, and case studies, this reprint is dedicated to the development of innovative solutions that improve healthcare and education for all. The topics addressed in this Special Issue cover a wide range of areas, including data mining, machine learning, learning analytics, prediction methods, pattern recognition, decision analysis, probabilistic reasoning, fuzzy systems, student or patient modelling, adaptive systems, collaborative systems, recommendation systems, experimental design, and empirical study cases. We hope that this reprint will enable the scientific community in both medicine and education to leverage the techniques from statistics and artificial intelligence to drive significant advances in their respective fields. These approaches hold promise for improving patient outcomes and enhancing the quality of education for students around the world.
Physical Description:1 electronic resource (406 p.)
ISBN:books978-3-0365-7247-5
9783036572468
9783036572475
Access:Open Access