"This book covers applications of artificial neural networks (ANN) and machine learning (ML) aspects of artificial intelligence to applications to the biomedical and business world including their interface to applications for screening for diseases to applications to large-scale credit card pu...

Ausführliche Beschreibung

Bibliographische Detailangaben

Weitere beteiligte Personen:	Niu, Gao (HerausgeberIn), Segall, Richard S. 1949- (HerausgeberIn)
Format:	Elektronisch E-Book
Sprache:	Englisch
Veröffentlicht:	Hershey, Pennsylvania IGI Global [2022]
Schlagwörter:	Medicine > Research > Data processing Neural networks (Computer science) Maschinelles Lernen Medizin
Links:	https://doi.org/10.4018/978-1-7998-8455-2 https://doi.org/10.4018/978-1-7998-8455-2 https://doi.org/10.4018/978-1-7998-8455-2 https://doi.org/10.4018/978-1-7998-8455-2 https://doi.org/10.4018/978-1-7998-8455-2 https://doi.org/10.4018/978-1-7998-8455-2 https://doi.org/10.4018/978-1-7998-8455-2
Zusammenfassung:	"This book covers applications of artificial neural networks (ANN) and machine learning (ML) aspects of artificial intelligence to applications to the biomedical and business world including their interface to applications for screening for diseases to applications to large-scale credit card purchasing patterns.
Beschreibung:	Includes bibliographical references and index Section 1. Introduction. Chapter 1. Overview of multi-factor prediction using deep neural networks, machine learning, and their open-source software -- Section 2. Biomedical applications. Chapter 2. Survey of applications of neural networks and machine learning to COVID-19 predictions ; Chapter 3. Comparing deep neural networks and gradient boosting for pneumonia detection using chest x-rays ; Chapter 4. Cardiovascular applications of artificial intelligence in research, diagnosis, and disease management ; Chapter 5. Predictions for COVID-19 with deep learning models of long short-term memory (LSTM) ; Chapter 6. Protein-protein interactions (PPI) via deep neural network (DNN) ; Chapter 7. US medical expense analysis through frequency and severity bootstrapping and regression model -- Section 3. Business applications. Chapter 8. Airbnb (air bed and breakfast) listing analysis through machine learning techniques ; Chapter 9. Automobile fatal accident and insurance claim analysis through artificial neural network ; Chapter 10. U.S. unemployment rate prediction by economic indices in the COVID-19 pandemic using neural network, random forest, and generalized linear regression ; Chapter 11. Applying machine learning methods for credit card payment default prediction with cost savings ; Chapter 12. Inflation rate modelling through a hybrid model of seasonal autoregressive moving average and multilayer perceptron neural network ; Chapter 13. Value analysis and prediction through machine learning techniques for popular basketball brands. - Mode of access: World Wide Web
Umfang:	1 Online-Ressource (394 Seiten)
ISBN:	9781799884576
DOI:	10.4018/978-1-7998-8455-2