| Record Type: |
Electronic resources
: Monograph/item
|
| [NT 15000414]: |
610.285 |
| Title/Author: |
Handbook of research on advancement of artificial intelligence in healthcare engineering/ Dilip Singh Sisodia, Ram Bilas Pachori, Lalit Garg, editors. |
| other author: |
Sisodia, Dilip Singh, |
| Published: |
Hershey, Pennsylvania : : IGI Global,, 2020. |
| Description: |
1 online resource (xxvii, 420 p.) |
| Subject: |
Artificial intelligence. |
| Subject: |
Medical informatics. |
| Subject: |
Biomedical engineering. |
| ISBN: |
9781799821229 (ebk.) |
| ISBN: |
9781799821205 (hbk.) |
| [NT 15000227]: |
Includes bibliographical references and index. |
| [NT 15000228]: |
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]: |
"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"-- |
| Online resource: |
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2120-5 |