Joarder Kamruzzaman – författare

The COVID-19 pandemic has significantly affected the healthcare sector across the globe. Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) play important roles when dealing with emerging challenges. These technologies are being applied to problems involving the early detection of infections, fast contact tracing, decision-making models, risk profiling of cohorts, and remote treatment. Applying these technologies runs against challenges including interoperability, lack of unified structure for eHealth, and data privacy and security. Emerging Technologies for Combatting Pandemics: AI, IoMT, and Analytics examines multiple models and solutions for various settings including individual, home, work, and society. The world’s healthcare systems are battling the novel coronavirus, and government authorities, scientists, medical practitioners, and medical services are striving hard to surmount these challenges.

This book focuses on the design and implementation of AI-based approaches in the proposed COVID-19 solutions that are enabled and supported by IoMT, sensor networks, cloud and edge computing, robotics, and analytics. It covers technologies under the umbrella of AI that include data science, big data, machine learning (ML), semantic technologies, analytics, and cyber security.

Highlights of the book include:

Epidemic forecasting models Surveillance and tracking systems IoMT and Internet of Healthcare Things-based integrated systems for COVID-19 Social network analysis systems Radiological image- based diagnosis systems Computational intelligence methods

This reference work is beneficial for interdisciplinary students, researchers, and healthcare and technology professionals who need to know how computational intelligence could be used for surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease.

The COVID-19 pandemic has significantly affected the healthcare sector across the globe. Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) play important roles when dealing with emerging challenges. These technologies are being applied to problems involving the early detection of infections, fast contact tracing, decision-making models, risk profiling of cohorts, and remote treatment. Applying these technologies runs against challenges including interoperability, lack of unified structure for eHealth, and data privacy and security. Emerging Technologies for Combatting Pandemics: AI, IoMT, and Analytics examines multiple models and solutions for various settings including individual, home, work, and society. The world’s healthcare systems are battling the novel coronavirus, and government authorities, scientists, medical practitioners, and medical services are striving hard to surmount these challenges.

This book focuses on the design and implementation of AI-based approaches in the proposed COVID-19 solutions that are enabled and supported by IoMT, sensor networks, cloud and edge computing, robotics, and analytics. It covers technologies under the umbrella of AI that include data science, big data, machine learning (ML), semantic technologies, analytics, and cyber security.

Highlights of the book include:

Epidemic forecasting models Surveillance and tracking systems IoMT and Internet of Healthcare Things-based integrated systems for COVID-19 Social network analysis systems Radiological image- based diagnosis systems Computational intelligence methods

This reference work is beneficial for interdisciplinary students, researchers, and healthcare and technology professionals who need to know how computational intelligence could be used for surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease.

The COVID-19 pandemic has significantly affected the healthcare sector across the globe. Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) play important roles when dealing with emerging challenges. These technologies are being applied to problems involving the early detection of infections, fast contact tracing, decision-making models, risk profiling of cohorts, and remote treatment. Applying these technologies runs against challenges including interoperability, lack of unified structure for eHealth, and data privacy and security. Emerging Technologies for Combatting Pandemics: AI, IoMT, and Analytics examines multiple models and solutions for various settings including individual, home, work, and society. The world’s healthcare systems are battling the novel coronavirus, and government authorities, scientists, medical practitioners, and medical services are striving hard to surmount these challenges.This book focuses on the design and implementation of AI-based approaches in the proposed COVID-19 solutions that are enabled and supported by IoMT, sensor networks, cloud and edge computing, robotics, and analytics. It covers technologies under the umbrella of AI that include data science, big data, machine learning (ML), semantic technologies, analytics, and cyber security.Highlights of the book include:Epidemic forecasting modelsSurveillance and tracking systemsIoMT and Internet of Healthcare Things-based integrated systems for COVID-19Social network analysis systemsRadiological image- based diagnosis systemsComputational intelligence methodsThis reference work is beneficial for interdisciplinary students, researchers, and healthcare and technology professionals who need to know how computational intelligence could be used for surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease.

The COVID-19 pandemic has significantly affected the healthcare sector across the globe. Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) play important roles when dealing with emerging challenges. These technologies are being applied to problems involving the early detection of infections, fast contact tracing, decision-making models, risk profiling of cohorts, and remote treatment. Applying these technologies runs against challenges including interoperability, lack of unified structure for eHealth, and data privacy and security. Emerging Technologies for Combatting Pandemics: AI, IoMT, and Analytics examines multiple models and solutions for various settings including individual, home, work, and society. The world’s healthcare systems are battling the novel coronavirus, and government authorities, scientists, medical practitioners, and medical services are striving hard to surmount these challenges.This book focuses on the design and implementation of AI-based approaches in the proposed COVID-19 solutions that are enabled and supported by IoMT, sensor networks, cloud and edge computing, robotics, and analytics. It covers technologies under the umbrella of AI that include data science, big data, machine learning (ML), semantic technologies, analytics, and cyber security.Highlights of the book include:Epidemic forecasting modelsSurveillance and tracking systemsIoMT and Internet of Healthcare Things-based integrated systems for COVID-19Social network analysis systemsRadiological image- based diagnosis systemsComputational intelligence methodsThis reference work is beneficial for interdisciplinary students, researchers, and healthcare and technology professionals who need to know how computational intelligence could be used for surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease.

This book constitutes the refereed post-conference proceedings of the Fourth International Conference on Applied Intelligence and Informatics, AII 2024, held in London, United Kingdom, during December 18–20, 2024.The 34 full papers included in these proceedings were carefully reviewed and selected from 118 submissions. They are organized in these topical sections as follows:Application of AI and Informatics in Pattern Recognition and Application of AI and Informatics in Network, Security,and Analytics.Chapter "e;34"e; is available open access under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License via link.springer.com.