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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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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Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a 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. 
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653 |a poisson distribution 
653 |a D-optimization 
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653 |a text analysis 
653 |a remote rehabilitation 
653 |a recommender system 
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653 |a collaborative work 
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653 |a group formation 
653 |a personality traits 
653 |a computer-supported cooperative learning 
653 |a non-parametric statistics 
653 |a predictive methods 
653 |a supervised classification 
653 |a random methods 
653 |a after-school exercise 
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653 |a structural relationship 
653 |a quantile regression 
653 |a instrumental variable quantile regression 
653 |a vitamin D 
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653 |a anthropometric parameters 
653 |a optimal experimental design 
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653 |a impedance spectroscopy 
653 |a algorithm 
653 |a competency-based model 
653 |a didactic planning 
653 |a ontology 
653 |a natural language processing 
653 |a Bloom's taxonomy 
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653 |a retinal disorders 
653 |a semantic segmentation 
653 |a learning behavior 
653 |a student performance prediction 
653 |a deep neural network (DNN) 
653 |a recurrent neural network (RNN) 
653 |a educational data mining (EDM) 
653 |a probabilistic graphical models 
653 |a bayesian networks 
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653 |a electrocardiogram signal 
653 |a discriminative convolutional sparse coding 
653 |a dictionary filter learning 
653 |a linear SVM 
653 |a student dropout 
653 |a Feature Selection 
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653 |a Support Vector Machines 
653 |a decision trees 
653 |a logistic regression 
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653 |a signal analysis 
653 |a classification 
653 |a OpenMarkov 
653 |a Bayesian Networks 
653 |a d-separation 
653 |a inference 
653 |a Learning Bayesian Networks 
653 |a continuous assessment 
653 |a Bayesian networks 
653 |a artificial neural networks 
653 |a influenza-like illness 
653 |a COVID-19 
653 |a Arabic sentiment analysis 
653 |a disease classification 
653 |a Facebook 
653 |a Algerian dialect 
653 |a mobile computing 
653 |a dual tasking 
653 |a cognitive decline 
653 |a human motion tracking 
653 |a gait analysis 
653 |a n/a 
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