Artificial Intelligence for the Internet of Health Things: Biomedical and Robotics Healthcare
Autor K. Shankar, Eswaran Perumal, Deepak Guptaen Limba Engleză Paperback – 25 sep 2023
- Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector
- Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms
- Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare
- Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks
- Introduces a new applications and case studies across all areas of AI in healthcare data
Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India.
Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (1) | 366.02 lei 43-57 zile | |
| CRC Press – 25 sep 2023 | 366.02 lei 43-57 zile | |
| Hardback (1) | 912.56 lei 43-57 zile | |
| CRC Press – 10 mai 2021 | 912.56 lei 43-57 zile |
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Specificații
ISBN-13: 9780367746902
ISBN-10: 0367746905
Pagini: 216
Ilustrații: 18 Tables, black and white; 75 Line drawings, black and white; 21 Halftones, black and white; 96 Illustrations, black and white
Dimensiuni: 156 x 234 x 12 mm
Greutate: 0.45 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Biomedical and Robotics Healthcare
ISBN-10: 0367746905
Pagini: 216
Ilustrații: 18 Tables, black and white; 75 Line drawings, black and white; 21 Halftones, black and white; 96 Illustrations, black and white
Dimensiuni: 156 x 234 x 12 mm
Greutate: 0.45 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Biomedical and Robotics Healthcare
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Public țintă
Academic and Professional Practice & DevelopmentCuprins
1. Artificial Intelligence (AI) for IoHT – an Introduction.
2. Role of Internet of Things and Cloud Computing Technologies in the Healthcare Sector.
3. An Extensive Overview of Wearable Technologies in Healthcare Sector.
4. IoHT and Cloud-Based Disease Diagnosis Model Using Particle Swarm Optimization with Artificial Neural Networks.
5. IoHT-Based Improved Grey Optimization with Support Vector Machine for Gastrointestinal Hemorrhage Detection and Diagnosis Model.
6. An Effective-Based Personalized Medicine Recommendation System Using Ensemble of Extreme Learning Machine Model.
7. A Novel Map Reduce-Based Hybrid Decision Tree with TFIDF Algorithm for Public Sentiment Mining of Diabetes Mellitus.
8. IoHT with Artificial Intelligence-Based Breast Cancer Diagnosis Model.
9. Artificial Intelligence with Cloud-Based Medical Image Retrieval System Using Deep Neural Network.
10. IoHT with Cloud-Based Brain Tumor Detection Using Particle Swarm Optimization with Support Vector Machine.
11. Artificial Intelligence-Based Hough Transform with an Adaptive Neuro-Fuzzy Inference System for a Diabetic Retinopathy Classification Model.
12. An IoHT-Based Intelligent Skin Lesion Detection and Classification Model in Dermoscopic Images.
13. An IoHT-Based Image Compression Model Using Modified Cuckoo Search Algorithm with Vector Quantization.
14. An Effective Secure Medical Image Transmission Using Improved Particle Swarm Optimization and Wavelet Transform.
15. IoHT with Wearable Devices-Based Feature Extraction and Deep Neural Networks Classification Model for Heart Disease Diagnosis
2. Role of Internet of Things and Cloud Computing Technologies in the Healthcare Sector.
3. An Extensive Overview of Wearable Technologies in Healthcare Sector.
4. IoHT and Cloud-Based Disease Diagnosis Model Using Particle Swarm Optimization with Artificial Neural Networks.
5. IoHT-Based Improved Grey Optimization with Support Vector Machine for Gastrointestinal Hemorrhage Detection and Diagnosis Model.
6. An Effective-Based Personalized Medicine Recommendation System Using Ensemble of Extreme Learning Machine Model.
7. A Novel Map Reduce-Based Hybrid Decision Tree with TFIDF Algorithm for Public Sentiment Mining of Diabetes Mellitus.
8. IoHT with Artificial Intelligence-Based Breast Cancer Diagnosis Model.
9. Artificial Intelligence with Cloud-Based Medical Image Retrieval System Using Deep Neural Network.
10. IoHT with Cloud-Based Brain Tumor Detection Using Particle Swarm Optimization with Support Vector Machine.
11. Artificial Intelligence-Based Hough Transform with an Adaptive Neuro-Fuzzy Inference System for a Diabetic Retinopathy Classification Model.
12. An IoHT-Based Intelligent Skin Lesion Detection and Classification Model in Dermoscopic Images.
13. An IoHT-Based Image Compression Model Using Modified Cuckoo Search Algorithm with Vector Quantization.
14. An Effective Secure Medical Image Transmission Using Improved Particle Swarm Optimization and Wavelet Transform.
15. IoHT with Wearable Devices-Based Feature Extraction and Deep Neural Networks Classification Model for Heart Disease Diagnosis
Notă biografică
K. Shankar (Member, IEEE) is a Postdoctoral Fellow of Department of Computer Applications, Alagappa University, Karaikudi, India.
Eswaran Perumal is working as an Assistant Professor of Department of Computer Applications, Alagappa University, Karaikudi, India.
Dr. Deepak Gupta is working as an Assistant Professor of Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.
Eswaran Perumal is working as an Assistant Professor of Department of Computer Applications, Alagappa University, Karaikudi, India.
Dr. Deepak Gupta is working as an Assistant Professor of Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.
Descriere
This book discusses research of Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions.