Next Generation Healthcare Systems Using Soft Computing Techniques (eBook, PDF)
Redaktion: Janghel, Rekh Ram; Raja, Hiral; Cengiz, Korhan; Raja, Rohit
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Next Generation Healthcare Systems Using Soft Computing Techniques (eBook, PDF)
Redaktion: Janghel, Rekh Ram; Raja, Hiral; Cengiz, Korhan; Raja, Rohit
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Written as a guide for assessing the roles that these technqiues play, the book highlights implementation strategies, problem solving solutions, and paves the way for future research endeavors in smart and next generation healthcare systems.
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Written as a guide for assessing the roles that these technqiues play, the book highlights implementation strategies, problem solving solutions, and paves the way for future research endeavors in smart and next generation healthcare systems.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 224
- Erscheinungstermin: 21. September 2022
- Englisch
- ISBN-13: 9781000653366
- Artikelnr.: 64552654
- Verlag: Taylor & Francis
- Seitenzahl: 224
- Erscheinungstermin: 21. September 2022
- Englisch
- ISBN-13: 9781000653366
- Artikelnr.: 64552654
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Rekh Ram Janghel, Hiral Raja
1. Computational Intelligence for Healthcare. 2. Analysis of Recurrent
Neural Network and Convolution Neural Network Techniques in Blood Cell
Classification. Chapter 3. Evaluating the Effectiveness of the Convolution
Neural Network in Detecting Brain Tumors. Chapter 4. Implementation of
Machine Learning in Color Perception and Psychology: A Review. Chapter 5.
Early Recognition of Dynamic Sleeping Patterns Associated with Rapid
Eyeball Movement Sleep Behavior Disorder of Apnea Pateants Using Neural
Network Techniques. Chapter 6. Smart Attendance cum Health Check-up Machine
for Students/Villagers/Company Employees. Chapter 7. Oral Histopathological
Photomicrograph Classification Using Deep Learning. Chapter 8. Prediction
of Stage of Alzheimer's Disease DenseNet Deep Learning Model. Chapter 9. An
Insight of Deep Learning Applications in the Healthcare Industry. Chapter
10. Expand Patient Care with AWS Cloud for Remote Medical Monitoring.
Chapter 11. Privacy and Security Solution in Wireless Sensor Network for
IoT in Healthcare System. Chapter 12. An Epileptic Seizure Detection and
Classification Based on Machine Learning Techniques. Chapter 13. Analysis
of Coronary Artery Disease Using Various Machine Learning Techniques.
Neural Network and Convolution Neural Network Techniques in Blood Cell
Classification. Chapter 3. Evaluating the Effectiveness of the Convolution
Neural Network in Detecting Brain Tumors. Chapter 4. Implementation of
Machine Learning in Color Perception and Psychology: A Review. Chapter 5.
Early Recognition of Dynamic Sleeping Patterns Associated with Rapid
Eyeball Movement Sleep Behavior Disorder of Apnea Pateants Using Neural
Network Techniques. Chapter 6. Smart Attendance cum Health Check-up Machine
for Students/Villagers/Company Employees. Chapter 7. Oral Histopathological
Photomicrograph Classification Using Deep Learning. Chapter 8. Prediction
of Stage of Alzheimer's Disease DenseNet Deep Learning Model. Chapter 9. An
Insight of Deep Learning Applications in the Healthcare Industry. Chapter
10. Expand Patient Care with AWS Cloud for Remote Medical Monitoring.
Chapter 11. Privacy and Security Solution in Wireless Sensor Network for
IoT in Healthcare System. Chapter 12. An Epileptic Seizure Detection and
Classification Based on Machine Learning Techniques. Chapter 13. Analysis
of Coronary Artery Disease Using Various Machine Learning Techniques.
1. Computational Intelligence for Healthcare. 2. Analysis of Recurrent
Neural Network and Convolution Neural Network Techniques in Blood Cell
Classification. Chapter 3. Evaluating the Effectiveness of the Convolution
Neural Network in Detecting Brain Tumors. Chapter 4. Implementation of
Machine Learning in Color Perception and Psychology: A Review. Chapter 5.
Early Recognition of Dynamic Sleeping Patterns Associated with Rapid
Eyeball Movement Sleep Behavior Disorder of Apnea Pateants Using Neural
Network Techniques. Chapter 6. Smart Attendance cum Health Check-up Machine
for Students/Villagers/Company Employees. Chapter 7. Oral Histopathological
Photomicrograph Classification Using Deep Learning. Chapter 8. Prediction
of Stage of Alzheimer's Disease DenseNet Deep Learning Model. Chapter 9. An
Insight of Deep Learning Applications in the Healthcare Industry. Chapter
10. Expand Patient Care with AWS Cloud for Remote Medical Monitoring.
Chapter 11. Privacy and Security Solution in Wireless Sensor Network for
IoT in Healthcare System. Chapter 12. An Epileptic Seizure Detection and
Classification Based on Machine Learning Techniques. Chapter 13. Analysis
of Coronary Artery Disease Using Various Machine Learning Techniques.
Neural Network and Convolution Neural Network Techniques in Blood Cell
Classification. Chapter 3. Evaluating the Effectiveness of the Convolution
Neural Network in Detecting Brain Tumors. Chapter 4. Implementation of
Machine Learning in Color Perception and Psychology: A Review. Chapter 5.
Early Recognition of Dynamic Sleeping Patterns Associated with Rapid
Eyeball Movement Sleep Behavior Disorder of Apnea Pateants Using Neural
Network Techniques. Chapter 6. Smart Attendance cum Health Check-up Machine
for Students/Villagers/Company Employees. Chapter 7. Oral Histopathological
Photomicrograph Classification Using Deep Learning. Chapter 8. Prediction
of Stage of Alzheimer's Disease DenseNet Deep Learning Model. Chapter 9. An
Insight of Deep Learning Applications in the Healthcare Industry. Chapter
10. Expand Patient Care with AWS Cloud for Remote Medical Monitoring.
Chapter 11. Privacy and Security Solution in Wireless Sensor Network for
IoT in Healthcare System. Chapter 12. An Epileptic Seizure Detection and
Classification Based on Machine Learning Techniques. Chapter 13. Analysis
of Coronary Artery Disease Using Various Machine Learning Techniques.