Biomedical and business applications using artificial neural networks and machine learning:
"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...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
[2022]
|
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| 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: | 26 PDFs (394 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781799884576 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
MARC
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| 245 | 0 | 0 | |a Biomedical and business applications using artificial neural networks and machine learning |c Richard S. Segall and Gao Niu, editor. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c [2022] | |
| 300 | |a 26 PDFs (394 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 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. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "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." | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 12/16/2021). | ||
| 650 | 0 | |a Medicine |x Research |x Data processing. | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 653 | |a Applications of Machine Learning Methods. | ||
| 653 | |a Applications of Neural Networks and Machine Learning to COVID-19 Predictions. | ||
| 653 | |a Artificial Neural Networks. | ||
| 653 | |a Cardiovascular Applications of Artificial Intelligence. | ||
| 653 | |a Deep Learning Models. | ||
| 653 | |a Deep Neural Networks. | ||
| 653 | |a Image Identification and Damage Estimation Through Convolutional Neural Network. | ||
| 653 | |a Machine Learning Methods Comparison for Unemployment Rate Prediction. | ||
| 653 | |a Machine Learning Techniques. | ||
| 653 | |a Multilayer Perceptron Neural Network. | ||
| 653 | |a Neural Networks. | ||
| 653 | |a Open Source Software. | ||
| 653 | |a Protein-Protein Interactions via Deep Neural Network. | ||
| 700 | 1 | |a Niu, Gao |e editor | |
| 700 | 1 | |a Segall, Richard |e editor | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 1799884554 |z 9781799884552 |
| 966 | 4 | 0 | |l DE-862 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-8455-2 |3 Volltext |
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| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-862 | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00270789 |
|---|---|
| _version_ | 1826942600256421888 |
| adam_text | |
| any_adam_object | |
| author2 | Niu, Gao Segall, Richard |
| author2_role | edt edt |
| author2_variant | g n gn r s rs |
| author_facet | Niu, Gao Segall, Richard |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | R - Medicine |
| callnumber-label | R853 |
| callnumber-raw | R853.D37 B53 2022eb |
| callnumber-search | R853.D37 B53 2022eb |
| callnumber-sort | R 3853 D37 B53 42022EB |
| callnumber-subject | R - General Medicine |
| collection | ZDB-98-IGB |
| contents | 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. |
| ctrlnum | (CaBNVSL)slc00002068 (OCoLC)1289419120 |
| dewey-full | 610.285 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 610 - Medicine and health |
| dewey-raw | 610.285 |
| dewey-search | 610.285 |
| dewey-sort | 3610.285 |
| dewey-tens | 610 - Medicine and health |
| discipline | Medizin |
| format | Electronic eBook |
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| id | ZDB-98-IGB-00270789 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:35Z |
| institution | BVB |
| isbn | 9781799884576 |
| language | English |
| oclc_num | 1289419120 |
| open_access_boolean | |
| owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 26 PDFs (394 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | IGI Global |
| record_format | marc |
| spelling | Biomedical and business applications using artificial neural networks and machine learning Richard S. Segall and Gao Niu, editor. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global [2022] 26 PDFs (394 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier 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. Restricted to subscribers or individual electronic text purchasers. "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." Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 12/16/2021). Medicine Research Data processing. Neural networks (Computer science) Applications of Machine Learning Methods. Applications of Neural Networks and Machine Learning to COVID-19 Predictions. Artificial Neural Networks. Cardiovascular Applications of Artificial Intelligence. Deep Learning Models. Deep Neural Networks. Image Identification and Damage Estimation Through Convolutional Neural Network. Machine Learning Methods Comparison for Unemployment Rate Prediction. Machine Learning Techniques. Multilayer Perceptron Neural Network. Neural Networks. Open Source Software. Protein-Protein Interactions via Deep Neural Network. Niu, Gao editor Segall, Richard editor IGI Global, publisher. Print version: 1799884554 9781799884552 |
| spellingShingle | Biomedical and business applications using artificial neural networks and machine learning 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. Medicine Research Data processing. Neural networks (Computer science) |
| title | Biomedical and business applications using artificial neural networks and machine learning |
| title_auth | Biomedical and business applications using artificial neural networks and machine learning |
| title_exact_search | Biomedical and business applications using artificial neural networks and machine learning |
| title_full | Biomedical and business applications using artificial neural networks and machine learning Richard S. Segall and Gao Niu, editor. |
| title_fullStr | Biomedical and business applications using artificial neural networks and machine learning Richard S. Segall and Gao Niu, editor. |
| title_full_unstemmed | Biomedical and business applications using artificial neural networks and machine learning Richard S. Segall and Gao Niu, editor. |
| title_short | Biomedical and business applications using artificial neural networks and machine learning |
| title_sort | biomedical and business applications using artificial neural networks and machine learning |
| topic | Medicine Research Data processing. Neural networks (Computer science) |
| topic_facet | Medicine Research Data processing. Neural networks (Computer science) |
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