AIoT Innovations in Digital Health
Emerging Trends, Challenges, and Solutions
Herausgeber: Rahman, Hameedur; Yogamoorthi, Thiagarajan; Gupta, Shashi Kant; Hajjami, Salma El; Khan, Muhammad Adnan; Ullah, Inam; Khan, Inam Ullah
AIoT Innovations in Digital Health
Emerging Trends, Challenges, and Solutions
Herausgeber: Rahman, Hameedur; Yogamoorthi, Thiagarajan; Gupta, Shashi Kant; Hajjami, Salma El; Khan, Muhammad Adnan; Ullah, Inam; Khan, Inam Ullah
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AI innovations in digital health offer unprecedented opportunities to facilitate human health and provide tools and techniques that reduce overall costs. This book discusses the use of AI to improve diagnostic accuracy, the use of remote diagnostic tools, medical robotics applications, drug discovery, technology-driven solutions, and more.
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AI innovations in digital health offer unprecedented opportunities to facilitate human health and provide tools and techniques that reduce overall costs. This book discusses the use of AI to improve diagnostic accuracy, the use of remote diagnostic tools, medical robotics applications, drug discovery, technology-driven solutions, and more.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 208
- Erscheinungstermin: 20. März 2025
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032744414
- ISBN-10: 1032744413
- Artikelnr.: 71808338
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 208
- Erscheinungstermin: 20. März 2025
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032744414
- ISBN-10: 1032744413
- Artikelnr.: 71808338
Dr. Inam Ullah Khan is the Founder of the Internet of Flying Vehicles Lab at AI-EYS. Recently, he has been working as a Global Mentor/Guest Lecturer at Impact Xcelerator, IE School of Science and Technology, Madrid, Spain. Previously, he was working as a visiting researcher at King's College London, United Kingdom. Also, he was a faculty member at different universities in Pakistan including the Center for Emerging Sciences Engineering and Technology (CESET), Islamabad, Abdul Wali Khan University, Garden Campus, Timergara Campus, University of Swat & Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST), Islamabad Campus. Dr. Khan completed his Ph.D. in Electronics Engineering from the Department of Electronic Engineering, Isra University, Islamabad Campus, School of Engineering & Applied Sciences (SEAS). He earned his M.S. degree in Electronic Engineering at the Department of Electronic Engineering, Isra University, Islamabad Campus, School of Engineering & Applied Sciences (SEAS), and his undergraduate degree in Bachelor of Computer Science from Abdul Wali Khan University Mardan, Pakistan. He has authored/co-authored more than 50 research articles in reputable journals, conferences, and as book chapters. He has served in many international conferences as a session chair or technical program committee member. As well as serving as a Guest Editor with many prestigious international journals. His research interests include Network System Security, Intrusion Detection, Intrusion Prevention, cryptography, Optimization techniques, WSN, IoT, Mobile Ad Hoc Networks (MANETS), Flying Ad Hoc Networks, and Machine Learning. Dr. Salma El Hajjami (Eng., Ph.D.) is an Assistant Professor and Researcher at the Faculty of Science, Ibn Zohr University, Agadir, Morocco since 2021. She earned her Ph.D. 2021 in Computer Science, from the Laboratory of Artificial Intelligence, Data Science and Emerging Systems from ENSA, Sidi Mohammed Ben Abdellah University, Fez, Morocco. She is a Computer Science Engineer, who graduated in 2015 from the National School of Applied Sciences Fez, Morocco. She is a member of the International Association of Engineers (IAENG) and the International Association of Online Engineering. Dr. Salma has made contributions in the fields of Social Big Data, Semantics Analytics, Anomaly Detection, and Imbalanced Big Data published at international conferences and journals. Her main research topics are Machine Learning, Deep Learning, Imbalanced Big Data, Data Science, and Blockchain. Dr. Shashi Kant Gupta, Post-Doctoral Fellow and Researcher, Computer Science and Engineering, Eudoxia Research University, USA in collaboration with Eudoxia Research Centre, India. He has completed his Ph.D. in CSE from Integral University, Lucknow, UP, India, He is currently working as the Founder and CEO of CREP PVT. LTD., Lucknow, UP, India. He has been a member of Spectrum IEEE & Potentials Magazine IEEE since 2019 and many more international organizations for research activities and he is the Editor-in-Chief of the International Journal of Data Informatics and Intelligent Computing (IJDIIC). He has published many research papers in reputable international journals and has published many papers in National and International conferences as well as in Seminars. He has published many Indian patents in the fields of information technology, computer science, and management. One Indian patent is under grant approval, and he has many German patents with grants, He has more than 10 years of teaching experience 2 years of Industrial Experience, and more than 2 years as CEO and Founder of a firm. His main research work focuses on performance enhancement through Cloud computing, Big Data Analytics, IoT, and Computational Intelligence-based Education. Dr. Hameedur Rahman received a BS and MS degree in software engineering with multimedia from the Limkokwing University of Creative Technology, Malaysia, and a Ph.D. degree in Computer Science from the Faculty of Information Science and Technology, University of Kebangsaan Malaysia, Bangi, Malaysia. He has 10 years of industrial experience in multinational companies. Dr. Rahman is currently an Associate Professor at AIR University and senior Research Member of the Center for Artificial Intelligence Technology and Head of the Department of Computer Games Development. He received some international awards including the Itex Bronze Medal of Innovation, Malaysia, and the Winner of NASA Space App and Virtual Reality Arena. His research interests include the areas of augmented reality, virtual reality, image processing, cryptography, Natural Language Processing, Data Mining, mobile technology, artificial intelligence, automation, and medical radiological technology. Dr. Y. Thiagarajan, (MIE , MISTE), Atal Mentor of Change - currently working as an Associate Professor cum HoD in the Department of Electrical and Electronics Engineering, Christ College of Engineering and Technology, Puducherry, India. He has been teaching undergraduate students in Electrical and Electronics Engineering for the past 14 years and is a Member of the Board of Studies and in Doctoral Committee. Presently he is serving as an Editorial Board Member and Reviewer for various reputed journals. He is a Fellow member of the Solar Energy Society of India, a member - of the Institute of Engineers, a senior member - of theIRD, a Life member of ISTE, and in various Professional bodies. He is the Recipient of the Best Faculty Award 2019, Awarded by Vasavi International Trust. He has been selected as a Mentor for CSIR SRTP NEST 2020- (period: May-August 2020). To his credit, he has Received One Indian Patent Grant, One Australian Innovation Patent Grant, and One copyright Grant. His field of interest Includes IoT in Renewable energy, AI for E-vehicles, Microbial Fuel cell (PEM), Power converters and Energy Conservation, Fuel Cell Technology, and Biomedical Engineering. Dr. Inam Ullah received a B.Sc. degree in Electrical Engineering (Telecommunication) from the Department of Electrical Engineering, University of Science and Technology Bannu (USTB), KPK, Pakistan, in 2016 and a Master's and Ph.D. degree in Information and Communication Engineering from the College of Internet of Things (IoT) Engineering, Hohai University (HHU), Changzhou Campus, 213022, China, in 2018 and 2022, respectively. He completed his postdoc with Brain Korea 2021 at the Chungbuk Information Technology Education and Research Center, Chungbuk National University, Cheongju, S Korea, from Oct. 2022 to March 31, 2023. He is currently an Assistant Professor at the Department of Computer Engineering, Gachon University, S Korea. He has authored more than 70 peer-reviewed articles on various research topics and is the reviewer of many prominent journals, His awards and honors include the Best Student Award from the University of Science and Technology Bannu (USTB), KPK, Pakistan, in 2015 and the Prime Minister Laptop Scheme Award from the University of Science and Technology Bannu (USTB), KPK, Pakistan, in April 2015. Top-10 students award of the College of Internet of Things (IoT) Engineering, Hohai University, China in June 2019, Top-100 students award of Hohai University (HHU), China in June 2019, Jiangsu Province Distinguish International Students award (30,000 RMB) in 2019-2020, Certificate of Recognition from Hohai University (HHU), China in 2021 & 2022 both, Top-100 students award of Hohai University (HHU), China in May 2022, Top-10 Outstanding Students Award, Hohai University (HHU), China in June 2022, and Distinguished Alumni Award from University of Science and Technology Bannu (USTB), KPK, Pakistan in Oct. 2022. His research interests include Robotics, the Internet of Things (IoT), Wireless Sensor Networks (WSNs), Underwater Communication and Localization, Underwater Sensor Networks (USNs), Artificial Intelligence (AI), Big data, Deep learning, etc. Dr. Muhammad Adnan Khan (Senior Member, IEEE) is currently working as an Associate Professor in the School of Computing, Skyline University College, Sharjah, UAE. He completed his Ph.D. from ISRA University, Islamabad, Pakistan, by obtaining a scholarship award from the Higher Education Commission, Islamabad, Pakistan, in 2016. He also completed his MS & BS degrees from the International Islamic University, Islamabad, Pakistan by obtaining a scholarship award from the Punjab Information and Technology Board, Govt. of Punjab, Pakistan. Before joining Skyline University College, Khan worked in various academic and industrial roles in Pakistan and the Republic of Korea. He has been teaching graduate and undergraduate students in computer science and engineering for the past 15 years. He has published more than 240 research articles in reputed International Journals as well as International Conferences. Dr. Khan's research interests primarily include Machine Learning, Deep Learning, Applications of Computational Intelligence, Smart Health, Smart City, Federated Learning, Extreme Machine Learning, MUD, Image Processing and Medical Diagnosis, Channel Estimation in Multi-Carrier Communication Systems Using Soft computing, etc.
1. Sentiment Analysis of Users Tweets for Polarity Opinions Detection Using
Deep Learning for Health Care Service. 2. Non-Sorted Genetic Algorithm &
Logistic Regression (NSGA-LR) for Prediction of Heart Diseases. 3. An
Intelligent Hybrid Blockchain Mechanism for IoT-based Healthcare
Applications in Blood Cancer Recurrence Detection. 4. Comprehensive
Solution for The Management of Chronic Kidney Disease: Application of
IoT-assisted technology. 5. Privacy and Security Aspects of AI Related to
IOT in Healthcare Industry: Methods, Tools, Applications, Open
Challenges. 6. Ontology based experts system for lung cancer disease
diagnosis. 7. Identification of Brain Tumors in MRI Images Using Artificial
Intelligence of Things. 8. Transformative Insights: Image-based Breast
Cancer Detection and Severity Assessment through Advanced AI Techniques. 9.
Cognitive Machine Learning-based Intrusion Detection System for
Identification of Life-Threatening Diseases.
Deep Learning for Health Care Service. 2. Non-Sorted Genetic Algorithm &
Logistic Regression (NSGA-LR) for Prediction of Heart Diseases. 3. An
Intelligent Hybrid Blockchain Mechanism for IoT-based Healthcare
Applications in Blood Cancer Recurrence Detection. 4. Comprehensive
Solution for The Management of Chronic Kidney Disease: Application of
IoT-assisted technology. 5. Privacy and Security Aspects of AI Related to
IOT in Healthcare Industry: Methods, Tools, Applications, Open
Challenges. 6. Ontology based experts system for lung cancer disease
diagnosis. 7. Identification of Brain Tumors in MRI Images Using Artificial
Intelligence of Things. 8. Transformative Insights: Image-based Breast
Cancer Detection and Severity Assessment through Advanced AI Techniques. 9.
Cognitive Machine Learning-based Intrusion Detection System for
Identification of Life-Threatening Diseases.
1. Sentiment Analysis of Users Tweets for Polarity Opinions Detection Using
Deep Learning for Health Care Service. 2. Non-Sorted Genetic Algorithm &
Logistic Regression (NSGA-LR) for Prediction of Heart Diseases. 3. An
Intelligent Hybrid Blockchain Mechanism for IoT-based Healthcare
Applications in Blood Cancer Recurrence Detection. 4. Comprehensive
Solution for The Management of Chronic Kidney Disease: Application of
IoT-assisted technology. 5. Privacy and Security Aspects of AI Related to
IOT in Healthcare Industry: Methods, Tools, Applications, Open
Challenges. 6. Ontology based experts system for lung cancer disease
diagnosis. 7. Identification of Brain Tumors in MRI Images Using Artificial
Intelligence of Things. 8. Transformative Insights: Image-based Breast
Cancer Detection and Severity Assessment through Advanced AI Techniques. 9.
Cognitive Machine Learning-based Intrusion Detection System for
Identification of Life-Threatening Diseases.
Deep Learning for Health Care Service. 2. Non-Sorted Genetic Algorithm &
Logistic Regression (NSGA-LR) for Prediction of Heart Diseases. 3. An
Intelligent Hybrid Blockchain Mechanism for IoT-based Healthcare
Applications in Blood Cancer Recurrence Detection. 4. Comprehensive
Solution for The Management of Chronic Kidney Disease: Application of
IoT-assisted technology. 5. Privacy and Security Aspects of AI Related to
IOT in Healthcare Industry: Methods, Tools, Applications, Open
Challenges. 6. Ontology based experts system for lung cancer disease
diagnosis. 7. Identification of Brain Tumors in MRI Images Using Artificial
Intelligence of Things. 8. Transformative Insights: Image-based Breast
Cancer Detection and Severity Assessment through Advanced AI Techniques. 9.
Cognitive Machine Learning-based Intrusion Detection System for
Identification of Life-Threatening Diseases.