Recent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices
- 1st Edition - June 1, 2025
- Imprint: Academic Press
- Editors: Aditya Khamparia, Deepak Gupta
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 3 0 1 2 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 3 0 1 3 - 1
Recent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices focuses on the intersection of biometric-driven computational approaches and techni… Read more
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Request a sales quoteRecent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices focuses on the intersection of biometric-driven computational approaches and techniques within a connected multi-modal environment, particularly emphasizing their applications in healthcare. The book explores cutting-edge methodological approaches that leverage technologies like blockchain and integrate them with information fusion, data security for medical devices, and trust management. Readers with find this to be a comprehensive overview of the topics covered, including machine learning and deep learning for biomedical-based biometrics, computational medical imaging techniques, security strategies for healthcare systems, AI technology for multimodal biometrics, and feature reduction techniques.
Other sections cover blockchain and fog computing models for medical sensor data storage and evolutionary optimization for biometric feature identification and recognition, amongst others.
Other sections cover blockchain and fog computing models for medical sensor data storage and evolutionary optimization for biometric feature identification and recognition, amongst others.
- Covers recent computational advancements in biomedical-driven biometrics for connected healthcare
- Explores intelligent computational multimodal technologies for healthcare, incorporating deep learning, parallel computing, and distributed computing
- Presents security aspects of next-generation healthcare technologies, including machine learning, deep learning, and blockchain integration with IoT for information fusion, data security, and trust management
- Provides both fundamental and high-level concepts, making it suitable for both industry professionals and beginners
- Includes applications of cloud and pervasive computing technologies in biometrics for real-world scenarios
Researchers, professionals from the fields of biomedical engineering, computer science and engineering, electrical-electronics engineering, mechanical engineering, cyber security, and informatics
1. Anomaly Detection in IoT using Fox Swarm Intelligence
2. Computational Medical Imaging for Biometrics using MRI and X-ray
3. AI Cybersecurity in Healthcare for Cyber-Physical Systems
4. Securing Healthcare Systems using Biometrics: A State-of-the-Art Systematic Literature Review and Future Research Directions
5. Social Media Analytics Using Deep Neural Networks for Mental Healthcare Applications
6. Energy Efficiency in IoT-based WSNs
7. Predictive Detection of Breast Cancer with Artificial Neural Network and Support Vector Machine
8. Evolutionary Optimization for Biometric Feature Identification and Recognition: A Survey
9. Comparative Analysis of Explainable Artificial Intelligence (XAI) Techniques on Cancer Dataset- addressing the “Black Box Problem”
10. Risk Monitoring Strategy for Confidentiality of Healthcare Information
11. Security Vulnerabilities against Fingerprint Biometric Systems
12. Adaptalytics of Students’ To Online Learning Using Machine Learning Classifiers And Sequential Neural Network
13. A Survey on Suicidal Rate Trends in Society using Machine Learning Models
14. AI assisted Wireless Capsule Endoscopy Devices for Gastrointestinal Tract Screening: A Review
2. Computational Medical Imaging for Biometrics using MRI and X-ray
3. AI Cybersecurity in Healthcare for Cyber-Physical Systems
4. Securing Healthcare Systems using Biometrics: A State-of-the-Art Systematic Literature Review and Future Research Directions
5. Social Media Analytics Using Deep Neural Networks for Mental Healthcare Applications
6. Energy Efficiency in IoT-based WSNs
7. Predictive Detection of Breast Cancer with Artificial Neural Network and Support Vector Machine
8. Evolutionary Optimization for Biometric Feature Identification and Recognition: A Survey
9. Comparative Analysis of Explainable Artificial Intelligence (XAI) Techniques on Cancer Dataset- addressing the “Black Box Problem”
10. Risk Monitoring Strategy for Confidentiality of Healthcare Information
11. Security Vulnerabilities against Fingerprint Biometric Systems
12. Adaptalytics of Students’ To Online Learning Using Machine Learning Classifiers And Sequential Neural Network
13. A Survey on Suicidal Rate Trends in Society using Machine Learning Models
14. AI assisted Wireless Capsule Endoscopy Devices for Gastrointestinal Tract Screening: A Review
- Edition: 1
- Published: June 1, 2025
- No. of pages (Paperback): 300
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780443330124
- eBook ISBN: 9780443330131
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Aditya Khamparia
Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision.
Affiliations and expertise
Assistant Professor, Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, IndiaDG
Deepak Gupta
Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision.
Affiliations and expertise
Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India