大葉大學圖書館 |

Handbook of research on advancement of artificial intelligence in healthcare engineering[electronic resource] /

レコード種別:	コンピュータ・メディア : 単行資料
[NT 15000414] null:	610.285
タイトル / 著者:	Handbook of research on advancement of artificial intelligence in healthcare engineering/ Dilip Singh Sisodia, Ram Bilas Pachori, Lalit Garg, editors.
その他の著者:	Sisodia, Dilip Singh,
出版された:	Hershey, Pennsylvania : : IGI Global,, 2020.
記述:	1 online resource (xxvii, 420 p.)
主題:	Artificial intelligence.
主題:	Medical informatics.
主題:	Biomedical engineering.
国際標準図書番号 (ISBN) :	9781799821229 (ebk.)
国際標準図書番号 (ISBN) :	9781799821205 (hbk.)
[NT 15000227] null:	Includes bibliographical references and index.
[NT 15000228] null:	Chapter 1. Automated seizure classification using deep neural network based on autoencoder -- Chapter 2. Automated detection of brain abnormalities using multi-directional features and randomized learning: a comparative study -- Chapter 3. A novel artificial intelligence technique for analysis of real-time electro-cardiogram signal for the prediction of early cardiac ailment onset -- Chapter 4. Epileptic seizure detection from EEG signals using bagged ensemble approach -- Chapter 5. Classification of epileptic seizure in EEG signal using support vector machine and EMD -- Chapter 6. Design of healthcare assistant using EEG signals for stress -- Chapter 7. Application of deep learning for EEG -- Chapter 8. AI-driven prognosis and diagnosis for personalized healthcare services: a predictive analytic perspective -- Chapter 9. A hybrid approach for 3D lung segmentation in CT images using active contour and morphological operation -- Chapter 10. Evolutionary intelligence-based feature descriptor selection for efficient identification of anti-cancer peptides -- Chapter 11. Optimizing the performance of devanagari script-based p300 speller system using binary PSO algorithm -- Chapter 12. Three channel wavelet filter banks with minimal time frequency spread for classification of seizure-free and seizure EEG signals -- Chapter 13. Recent studies and research on sickle cell disease: statistical analysis and machine learning approach -- Chapter 14. Heart sound data acquisition and preprocessing techniques: a review -- Chapter 15. Exhibiting app and analysis for biofeedback-based mental health analyzer -- Chapter 16. Computational approach for personality detection on attributes: an IoT-MMBD-enabled environment -- Chapter 17. Tension type headache: IOT and FOG applications in healthcare using different biofeedback -- Chapter 18. NLP for clinical data analysis: handling the unstructured clinical information.
[NT 15000229] null:	"This book explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, implementation, and optimization of challenging healthcare engineering solutions"--
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2120-5

Handbook of research on advancement of artificial intelligence in healthcare engineering[electronic resource] /
Handbook of research on advancement of artificial intelligence in healthcare engineering[electronic resource] /Dilip Singh Sisodia, Ram Bilas Pachori, Lalit Garg, editors. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (xxvii, 420 p.)

Includes bibliographical references and index.

Chapter 1. Automated seizure classification using deep neural network based on autoencoder -- Chapter 2. Automated detection of brain abnormalities using multi-directional features and randomized learning: a comparative study -- Chapter 3. A novel artificial intelligence technique for analysis of real-time electro-cardiogram signal for the prediction of early cardiac ailment onset -- Chapter 4. Epileptic seizure detection from EEG signals using bagged ensemble approach -- Chapter 5. Classification of epileptic seizure in EEG signal using support vector machine and EMD -- Chapter 6. Design of healthcare assistant using EEG signals for stress -- Chapter 7. Application of deep learning for EEG -- Chapter 8. AI-driven prognosis and diagnosis for personalized healthcare services: a predictive analytic perspective -- Chapter 9. A hybrid approach for 3D lung segmentation in CT images using active contour and morphological operation -- Chapter 10. Evolutionary intelligence-based feature descriptor selection for efficient identification of anti-cancer peptides -- Chapter 11. Optimizing the performance of devanagari script-based p300 speller system using binary PSO algorithm -- Chapter 12. Three channel wavelet filter banks with minimal time frequency spread for classification of seizure-free and seizure EEG signals -- Chapter 13. Recent studies and research on sickle cell disease: statistical analysis and machine learning approach -- Chapter 14. Heart sound data acquisition and preprocessing techniques: a review -- Chapter 15. Exhibiting app and analysis for biofeedback-based mental health analyzer -- Chapter 16. Computational approach for personality detection on attributes: an IoT-MMBD-enabled environment -- Chapter 17. Tension type headache: IOT and FOG applications in healthcare using different biofeedback -- Chapter 18. NLP for clinical data analysis: handling the unstructured clinical information.

Restricted to subscribers or individual electronic text purchasers.

"This book explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, implementation, and optimization of challenging healthcare engineering solutions"--

ISBN: 9781799821229 (ebk.)Subjects--Topical Terms:

172060
Artificial intelligence.

LC Class. No.: R855.3 / .H36 2020

Dewey Class. No.: 610.285

Handbook of research on advancement of artificial intelligence in healthcare engineering[electronic resource] /
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020 $a 9781799821205 (hbk.)
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245 0 0 $a Handbook of research on advancement of artificial intelligence in healthcare engineering $h [electronic resource] / $c Dilip Singh Sisodia, Ram Bilas Pachori, Lalit Garg, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2020.
300 $a 1 online resource (xxvii, 420 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Automated seizure classification using deep neural network based on autoencoder -- Chapter 2. Automated detection of brain abnormalities using multi-directional features and randomized learning: a comparative study -- Chapter 3. A novel artificial intelligence technique for analysis of real-time electro-cardiogram signal for the prediction of early cardiac ailment onset -- Chapter 4. Epileptic seizure detection from EEG signals using bagged ensemble approach -- Chapter 5. Classification of epileptic seizure in EEG signal using support vector machine and EMD -- Chapter 6. Design of healthcare assistant using EEG signals for stress -- Chapter 7. Application of deep learning for EEG -- Chapter 8. AI-driven prognosis and diagnosis for personalized healthcare services: a predictive analytic perspective -- Chapter 9. A hybrid approach for 3D lung segmentation in CT images using active contour and morphological operation -- Chapter 10. Evolutionary intelligence-based feature descriptor selection for efficient identification of anti-cancer peptides -- Chapter 11. Optimizing the performance of devanagari script-based p300 speller system using binary PSO algorithm -- Chapter 12. Three channel wavelet filter banks with minimal time frequency spread for classification of seizure-free and seizure EEG signals -- Chapter 13. Recent studies and research on sickle cell disease: statistical analysis and machine learning approach -- Chapter 14. Heart sound data acquisition and preprocessing techniques: a review -- Chapter 15. Exhibiting app and analysis for biofeedback-based mental health analyzer -- Chapter 16. Computational approach for personality detection on attributes: an IoT-MMBD-enabled environment -- Chapter 17. Tension type headache: IOT and FOG applications in healthcare using different biofeedback -- Chapter 18. NLP for clinical data analysis: handling the unstructured clinical information.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, implementation, and optimization of challenging healthcare engineering solutions"-- $c Provided by publisher.
650 0 $a Artificial intelligence. $3 172060
650 0 $a Medical informatics. $3 340360
650 0 $a Biomedical engineering. $3 750294
700 1 $a Sisodia, Dilip Singh, $d 1977- $3 750291
700 1 $a Pachori, Ram Bilas, $d 1979- $3 750292
700 1 $a Garg, Lalit, $d 1977- $3 750293
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2120-5