Md. Mehedi Hassan – författare
Visar alla böcker från författaren . Handla med fri frakt och snabb leverans.
20 produkter
20 produkter
Inbunden, Engelska, 2024
2 101 kr
Skickas inom 10-15 vardagar
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information.Features:Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications.Investigates privacy-preserving methods with emphasis on data security and privacy.Discusses healthcare scaling and resource efficiency considerations.Examines methods for sharing information among various healthcare organizations while retaining model performance.This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.
- Nyhet
Häftad, Engelska, 2026
810 kr
Skickas inom 10-15 vardagar
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information.Features:Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications.Investigates privacy-preserving methods with emphasis on data security and privacy.Discusses healthcare scaling and resource efficiency considerations.Examines methods for sharing information among various healthcare organizations while retaining model performance.This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.
E-bok
PDF, Engelska, 2024970 kr
Läs direkt efter köp
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information.
Features:
Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications. Investigates privacy-preserving methods with emphasis on data security and privacy. Discusses healthcare scaling and resource efficiency considerations. Examines methods for sharing information among various healthcare organizations while retaining model performance.This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.
E-bok
Engelska, 2024970 kr
Läs direkt efter köp
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information.
Features:
Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications. Investigates privacy-preserving methods with emphasis on data security and privacy. Discusses healthcare scaling and resource efficiency considerations. Examines methods for sharing information among various healthcare organizations while retaining model performance.This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.
E-bok
Engelska, 20251 844 kr
Läs direkt efter köp
This book is an in-depth exploration of brain networks, providing a comprehensive understanding of their structures, functions, and implications for personalization through artificial intelligence. Readers will gain insights into the intricate workings of the brain, making this book an indispensable resource for those seeking a thorough grasp of neuroscience concepts. It offers the seamless integration of neuroscience principles with artificial intelligence applications. The book bridges these two domains, elucidating how advancements in AI draw inspiration from the complexities of the human brain. This interdisciplinary approach sets the book apart, offering readers a holistic view of cutting-edge technologies. Readers can expect practical applications and real-world case studies that illustrate the tangible benefits of the concepts discussed. From personalized healthcare solutions to adaptive learning systems, the book goes beyond theory, empowering readers to apply knowledge in diverse domains. This practical emphasis enhances the book’s relevance for professionals and researchers alike. The inclusion of online enhancements, such as interactive visualizations, downloadable supplementary materials, and engaging video content, transforms the reading experience into an interactive learning journey. This added value distinguishes the book by providing readers with hands-on tools to deepen their understanding and apply newfound knowledge.
This book doesn’t just dwell on current technologies; it takes readers into the future by exploring emerging trends at the intersection of neuroscience and artificial intelligence. By delving into potential breakthroughs and innovations, the book equips readers with insights that are forward-thinking and relevant in an ever-evolving technological landscape.
E-bok
PDF, Engelska, 20262 072 kr
Läs direkt efter köp
Transforming Global Healthcare: The Role of AI and IoT in Modern Medical Systems explores the transformative potential of the integration of technologies such as AI, Big Data, IoT, and Blockchain in the healthcare sector. This comprehensive volume aims to illustrate how these advanced technologies can address sustainability challenges, improve decision-making processes, and enhance overall healthcare delivery. By mapping existing knowledge and forecasting future trends, the book provides a detailed roadmap for sustainable healthcare development.Key features include:- Explores AI, big data, IoT, and blockchain in healthcare in-depth.- Provides actionable strategies for energy management, waste disposal, and green supply chains- Provides in-depth coverage of real-time health monitoring, predictive analytics, robotic surgery, and AI medical imaging.- Provides insights into preventing drug counterfeiting, managing pharmaceutical cold chains, and optimizing supply chains.- Comprises a comparative analysis of global healthcare systems, telemedicine evolution, and future digital health trends.
2 072 kr
Läs direkt efter köp
Transforming Global Healthcare: The Role of AI and IoT in Modern Medical Systems explores the transformative potential of the integration of technologies such as AI, Big Data, IoT, and Blockchain in the healthcare sector. This comprehensive volume aims to illustrate how these advanced technologies can address sustainability challenges, improve decision-making processes, and enhance overall healthcare delivery. By mapping existing knowledge and forecasting future trends, the book provides a detailed roadmap for sustainable healthcare development.Key features include:- Explores AI, big data, IoT, and blockchain in healthcare in-depth.- Provides actionable strategies for energy management, waste disposal, and green supply chains- Provides in-depth coverage of real-time health monitoring, predictive analytics, robotic surgery, and AI medical imaging.- Provides insights into preventing drug counterfeiting, managing pharmaceutical cold chains, and optimizing supply chains.- Comprises a comparative analysis of global healthcare systems, telemedicine evolution, and future digital health trends.
1 986 kr
Läs direkt efter köp
This book delves into the transformative power of AI in the realm of neurodegenerative diseases,covering topics such as ALS, Huntington's, Parkinson's, and Alzheimer's. Generative AIprovides new opportunities for early diagnosis, precise therapy, and individualized rehabilitation,which are crucial as these conditions remain major obstacles for healthcare providersand researchers.Researchers, physicians, AI developers, and healthcare professionals will find this bookan invaluable resource for understanding how AI is influencing the development of treatmentsfor neurodegenerative diseases. It describes important obstacles and future directions whileproviding insights into the newest breakthroughs, thus bridging the gap between technologyand practical clinical applications. Anyone involved in neurodegenerative healthcare, fromscientists conducting AI-driven medical research to physicians seeking to incorporate AI intopatient care or AI professionals investigating new healthcare applications, will find the informationand insights they need in this comprehensive book.Predictive analytics, biomarker identification, and drug discovery are being transformedby AI-driven models, such as deep neural networks, generative adversarial networks (GANs),and variational autoencoders (VAEs). This book offers a comprehensive examination of thesedevelopments. Robots, wearable sensors, and cognitive therapy platforms are some of theAI-enhanced rehabilitation tools covered, as are AI-integrated cutting-edge technologies likefMRI and MRI, gene-editing methods like CRISPR, and more.In addition to discussing recent technical developments, this book takes a close look atthe data privacy, ethics, and regulatory issues that arise when using AI to study neurodegenerativedisorders. Issues like algorithmic bias, model explainability, and fair AI-driven healthcareare thoroughly investigated in light of the growing usage of AI models in clinical decision-making,mental health applications, and cognitive rehabilitation.
Inbunden, Engelska, 2026
1 800 kr
Skickas inom 10-15 vardagar
Transforming Global Healthcare: The Role of AI and IoT in Modern Medical Systems explores the transformative potential of the integration of technologies such as AI, Big Data, IoT, and Blockchain in the healthcare sector. This comprehensive volume aims to illustrate how these advanced technologies can address sustainability challenges, improve decision-making processes, and enhance overall healthcare delivery. By mapping existing knowledge and forecasting future trends, the book provides a detailed roadmap for sustainable healthcare development.Key features include:– Explores AI, big data, IoT, and blockchain in healthcare in-depth.– Provides actionable strategies for energy management, waste disposal, and green supply chains– Provides in-depth coverage of real-time health monitoring, predictive analytics, robotic surgery, and AI medical imaging.– Provides insights into preventing drug counterfeiting, managing pharmaceutical cold chains, and optimizing supply chains.– Comprises a comparative analysis of global healthcare systems, telemedicine evolution, and future digital health trends.
Inbunden, Engelska, 2025
2 352 kr
Skickas inom 5-8 vardagar
This proposed book provides deeper insights into artificial intelligence techniques and procedures available for earth sciences. This book unveils several applications of metaheuristic approaches (i.e., swarm intelligence and IoT technologies) in collaboration with AI for earth sciences. It presents the science behind smart technologies that reveal the power of artificial intelligence and IoT. These methodologies help to extract meaningful insights from earth sciences big data analytics. These advanced technologies used in earth science practices can remove geographical barriers, locally adaptive, operationally feasible, and economically affordable. The areas can be explored with the aim of digitizing the whole world. Technological advancement also impacts the financial aspect involved in managing the earth sciences. Intelligent AI applications have made significant strides in the field of earth sciences, offering novel solutions to complex challenges, driving impactful research, and revolutionizing data analysis and interpretation. This intersection of artificial intelligence and earth sciences has paved the way for an enhanced understanding of our planet and its various phenomena.
E-bok
Engelska, 20253 148 kr
Läs direkt efter köp
This proposed book provides deeper insights into artificial intelligence techniques and procedures available for earth sciences. This book unveils several applications of metaheuristic approaches (i.e., swarm intelligence and IoT technologies) in collaboration with AI for earth sciences. It presents the science behind smart technologies that reveal the power of artificial intelligence and IoT. These methodologies help to extract meaningful insights from earth sciences big data analytics. These advanced technologies used in earth science practices can remove geographical barriers, locally adaptive, operationally feasible, and economically affordable. The areas can be explored with the aim of digitizing the whole world. Technological advancement also impacts the financial aspect involved in managing the earth sciences. Intelligent AI applications have made significant strides in the field of earth sciences, offering novel solutions to complex challenges, driving impactful research, and revolutionizing data analysis and interpretation. This intersection of artificial intelligence and earth sciences has paved the way for an enhanced understanding of our planet and its various phenomena.
- Nyhet
Häftad, Engelska, 2026
2 356 kr
Skickas inom 10-15 vardagar
This proposed book provides deeper insights into artificial intelligence techniques and procedures available for earth sciences. This book unveils several applications of metaheuristic approaches (i.e., swarm intelligence and IoT technologies) in collaboration with AI for earth sciences. It presents the science behind smart technologies that reveal the power of artificial intelligence and IoT. These methodologies help to extract meaningful insights from earth sciences big data analytics. These advanced technologies used in earth science practices can remove geographical barriers, locally adaptive, operationally feasible, and economically affordable. The areas can be explored with the aim of digitizing the whole world. Technological advancement also impacts the financial aspect involved in managing the earth sciences. Intelligent AI applications have made significant strides in the field of earth sciences, offering novel solutions to complex challenges, driving impactful research, and revolutionizing data analysis and interpretation. This intersection of artificial intelligence and earth sciences has paved the way for an enhanced understanding of our planet and its various phenomena.
Inbunden, Engelska, 2025
1 986 kr
Skickas inom 10-15 vardagar
This book delves into the fundamental concepts, methodologies, and practical implementations of feature fusion, providing valuable perspectives on how merging several data aspects might augment the decision-making skills of artificial intelligence. Feature fusion is inherently connected to the advancement of intelligent solutions from medical data as it enables the incorporation of various and complementary data sources to construct more advanced AI models. Within the medical domain, data manifests in diverse formats, including electronic health records (EHRs), medical imaging, genomic data, and real-time sensor metrics. Although each of these data kinds offers distinct perspectives, they may have limitations in terms of their breadth or depth when considered independently. The application of feature fusion enables the integration of diverse data sources into a unified model, hence improving the AI's capacity to detect patterns, make precise predictions, and produce significant insights. The fusion process facilitates the development of intelligent solutions that exhibit enhanced reliability and effectiveness by using a more extensive reservoir of knowledge. For example, an artificial intelligence system that combines imaging data with clinical history might enhance the precision of disease diagnosis, forecast patient outcomes, and suggest tailored treatment strategies. Feature fusion is the crucial factor in unleashing the complete capabilities of medical data, enabling artificial intelligence to provide intelligent solutions that not only enhance the provision of healthcare but also stimulate advancements in medical research and practice. The proposed book explores the advanced notion of feature fusion within the field of artificial intelligence, with a particular emphasis on its implementation in physiological data. The integration of many data sources is crucial in the development of more precise, dependable, and understandable AI models as the healthcare industry becomes more data-driven.
E-bok
Engelska, 20252 592 kr
Läs direkt efter köp
This book delves into the fundamental concepts, methodologies, and practical implementations of feature fusion, providing valuable perspectives on how merging several data aspects might augment the decision-making skills of artificial intelligence. Feature fusion is inherently connected to the advancement of intelligent solutions from medical data as it enables the incorporation of various and complementary data sources to construct more advanced AI models. Within the medical domain, data manifests in diverse formats, including electronic health records (EHRs), medical imaging, genomic data, and real-time sensor metrics. Although each of these data kinds offers distinct perspectives, they may have limitations in terms of their breadth or depth when considered independently. The application of feature fusion enables the integration of diverse data sources into a unified model, hence improving the AI's capacity to detect patterns, make precise predictions, and produce significant insights. The fusion process facilitates the development of intelligent solutions that exhibit enhanced reliability and effectiveness by using a more extensive reservoir of knowledge. For example, an artificial intelligence system that combines imaging data with clinical history might enhance the precision of disease diagnosis, forecast patient outcomes, and suggest tailored treatment strategies. Feature fusion is the crucial factor in unleashing the complete capabilities of medical data, enabling artificial intelligence to provide intelligent solutions that not only enhance the provision of healthcare but also stimulate advancements in medical research and practice. The proposed book explores the advanced notion of feature fusion within the field of artificial intelligence, with a particular emphasis on its implementation in physiological data. The integration of many data sources is crucial in the development of more precise, dependable, and understandable AI models as the healthcare industry becomes more data-driven.
Inbunden, Engelska, 2025
2 202 kr
Skickas inom 10-15 vardagar
This book represents a unique and comprehensive resource for understanding the intersection of advanced artificial intelligence (AI) and neurology. By focusing on graph neural networks (GNNs), the book addresses a crucial gap in the current literature, providing valuable insights into the analysis and interpretation of complex brain networks and neurological data. Intended for a diverse audience, including clinicians, scientists, researchers, and students, it demystifies the complexities of GNNs and their applications in neurology. For clinicians and healthcare practitioners, the book illustrates how GNNs can enhance diagnostic accuracy, inform personalized treatment plans and predict disease progression. This leads to improved patient outcomes and a deeper understanding of neurological conditions such as Alzheimer's, Parkinson's, multiple sclerosis and epilepsy. Researchers will find the book particularly valuable as it delves into the methodologies and technical aspects of GNNs, showcasing their ability to handle diverse data sources including genetic, imaging and clinical information. By integrating these datasets, GNNs reveal hidden patterns and biomarkers, offering new avenues for research and potential therapeutic targets.A Guide to Graph Neural Networks for Neurological Disorders addresses the challenge of missing data, a common issue in neurological research, and demonstrates how GNNs can manage and mitigate these gaps. For students, both undergraduate and postgraduate, the book serves as an educational tool, providing clear explanations and practical examples that make complex concepts accessible. It equips the next generation of neuroscientists and data scientists with the knowledge and skills needed to contribute to this rapidly evolving field. The book aims to provide a foundational understanding of GNNs, demonstrate their practical applications in neurology, and inspire further research and innovation. By bridging the gap between AI and medical practice, the book empowers readers to leverage cutting-edge technology in the quest to understand and treat neurological illnesses, ultimately enhancing the quality of care and advancing the field of neuroscience.
E-bok
Engelska, 20252 833 kr
Läs direkt efter köp
This book represents a unique and comprehensive resource for understanding the intersection of advanced artificial intelligence (AI) and neurology. By focusing on graph neural networks (GNNs), the book addresses a crucial gap in the current literature, providing valuable insights into the analysis and interpretation of complex brain networks and neurological data. Intended for a diverse audience, including clinicians, scientists, researchers, and students, it demystifies the complexities of GNNs and their applications in neurology. For clinicians and healthcare practitioners, the book illustrates how GNNs can enhance diagnostic accuracy, inform personalized treatment plans and predict disease progression. This leads to improved patient outcomes and a deeper understanding of neurological conditions such as Alzheimer's, Parkinson's, multiple sclerosis and epilepsy. Researchers will find the book particularly valuable as it delves into the methodologies and technical aspects of GNNs, showcasing their ability to handle diverse data sources including genetic, imaging and clinical information. By integrating these datasets, GNNs reveal hidden patterns and biomarkers, offering new avenues for research and potential therapeutic targets.A Guide to Graph Neural Networks for Neurological Disorders addresses the challenge of missing data, a common issue in neurological research, and demonstrates how GNNs can manage and mitigate these gaps. For students, both undergraduate and postgraduate, the book serves as an educational tool, providing clear explanations and practical examples that make complex concepts accessible. It equips the next generation of neuroscientists and data scientists with the knowledge and skills needed to contribute to this rapidly evolving field. The book aims to provide a foundational understanding of GNNs, demonstrate their practical applications in neurology, and inspire further research and innovation. By bridging the gap between AI and medical practice, the book empowers readers to leverage cutting-edge technology in the quest to understand and treat neurological illnesses, ultimately enhancing the quality of care and advancing the field of neuroscience.
Del 77 - Information Systems Engineering and Management
Deep Learning in Cardiovascular Health
Sustainable Al Approaches for Heart Disease Diagnosis and Treatment
Inbunden, Engelska, 2026
2 206 kr
Skickas inom 10-15 vardagar
This book showcases the most recent developments in the application of artificial intelligence to cardiology and medical imaging, with an emphasis on precise diagnosis, early prediction, and patient-centered care. In order to overcome clinical data ambiguity and enhance confidence in automated systems, it presents innovative frameworks that combine deep learning, fuzzy graph neural networks, metaheuristic optimization, and explainable AI. This book bridges the gap between state-of-the-art research and practical healthcare applications by covering a wide range of techniques, including CNNs, RNNs, residual networks, federated learning, and multimodal learning. As a research reference and a manual for implementing AI-driven healthcare solutions, it provides useful tools, datasets, and methodologies that foster innovation in precision medicine and medical decision-making. It is designed for researchers, clinicians, and students.
E-bok
Engelska, 20262 917 kr
Läs direkt efter köp
This book showcases the most recent developments in the application of artificial intelligence to cardiology and medical imaging, with an emphasis on precise diagnosis, early prediction, and patient-centered care. In order to overcome clinical data ambiguity and enhance confidence in automated systems, it presents innovative frameworks that combine deep learning, fuzzy graph neural networks, metaheuristic optimization, and explainable AI. This book bridges the gap between state-of-the-art research and practical healthcare applications by covering a wide range of techniques, including CNNs, RNNs, residual networks, federated learning, and multimodal learning. As a research reference and a manual for implementing AI-driven healthcare solutions, it provides useful tools, datasets, and methodologies that foster innovation in precision medicine and medical decision-making. It is designed for researchers, clinicians, and students.
Inbunden, Engelska, 2025
1 656 kr
Skickas inom 10-15 vardagar
This book delves into the transformative power of AI in the realm of neurodegenerative diseases,covering topics such as ALS, Huntington’s, Parkinson’s, and Alzheimer’s. Generative AIprovides new opportunities for early diagnosis, precise therapy, and individualized rehabilitation,which are crucial as these conditions remain major obstacles for healthcare providersand researchers.Researchers, physicians, AI developers, and healthcare professionals will find this bookan invaluable resource for understanding how AI is influencing the development of treatmentsfor neurodegenerative diseases. It describes important obstacles and future directions whileproviding insights into the newest breakthroughs, thus bridging the gap between technologyand practical clinical applications. Anyone involved in neurodegenerative healthcare, fromscientists conducting AI-driven medical research to physicians seeking to incorporate AI intopatient care or AI professionals investigating new healthcare applications, will find the informationand insights they need in this comprehensive book.Predictive analytics, biomarker identification, and drug discovery are being transformedby AI-driven models, such as deep neural networks, generative adversarial networks (GANs),and variational autoencoders (VAEs). This book offers a comprehensive examination of thesedevelopments. Robots, wearable sensors, and cognitive therapy platforms are some of theAI-enhanced rehabilitation tools covered, as are AI-integrated cutting-edge technologies likefMRI and MRI, gene-editing methods like CRISPR, and more.In addition to discussing recent technical developments, this book takes a close look atthe data privacy, ethics, and regulatory issues that arise when using AI to study neurodegenerativedisorders. Issues like algorithmic bias, model explainability, and fair AI-driven healthcareare thoroughly investigated in light of the growing usage of AI models in clinical decision-making,mental health applications, and cognitive rehabilitation.
Inbunden, Engelska, 2025
1 539 kr
Skickas inom 10-15 vardagar
This book is an in-depth exploration of brain networks, providing a comprehensive understanding of their structures, functions, and implications for personalization through artificial intelligence. Readers will gain insights into the intricate workings of the brain, making this book an indispensable resource for those seeking a thorough grasp of neuroscience concepts. It offers the seamless integration of neuroscience principles with artificial intelligence applications. The book bridges these two domains, elucidating how advancements in AI draw inspiration from the complexities of the human brain. This interdisciplinary approach sets the book apart, offering readers a holistic view of cutting-edge technologies. Readers can expect practical applications and real-world case studies that illustrate the tangible benefits of the concepts discussed. From personalized healthcare solutions to adaptive learning systems, the book goes beyond theory, empowering readers to apply knowledge in diverse domains. This practical emphasis enhances the book’s relevance for professionals and researchers alike. The inclusion of online enhancements, such as interactive visualizations, downloadable supplementary materials, and engaging video content, transforms the reading experience into an interactive learning journey. This added value distinguishes the book by providing readers with hands-on tools to deepen their understanding and apply newfound knowledge.This book doesn’t just dwell on current technologies; it takes readers into the future by exploring emerging trends at the intersection of neuroscience and artificial intelligence. By delving into potential breakthroughs and innovations, the book equips readers with insights that are forward-thinking and relevant in an ever-evolving technological landscape.