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Bio-Inspired Optimization for Medical Data

Author: Sumit Srivastava

Publisher: Wiley-Scrivener

Published: 2024-08-06

Total Pages: 0

ISBN-13: 9781394214181

Bio-Inspired Optimization for Medical Data is a groundbreaking book that delves into the convergence of nature’s ingenious algorithms and cutting-edge healthcare technology. Through a comprehensive exploration of state-of-the-art algorithms and practical case studies, readers gain unparalleled insights into optimizing medical data processing, enabling more precise diagnosis, optimizing treatment plans, and ultimately advancing the field of healthcare. Organized into 15 chapters, readers learn about the theoretical foundation of pragmatic implementation strategies and actionable advice. In addition, it addresses current developments in molecular subtyping and how they can enhance clinical care. By bridging the gap between cutting-edge technology and critical healthcare challenges, this book is a pivotal contribution, providing a roadmap for leveraging nature-inspired algorithms. This is an indispensable resource that will drive significant changes in the healthcare sector.

Bio-Inspired Optimization for Medical Data Mining

Author: Sumit Srivastava

Publisher: John Wiley & Sons

Published: 2024-08-06

Total Pages: 340

ISBN-13: 1394214189

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This book is a comprehensive exploration of bio-inspired optimization techniques and their potential applications in healthcare. Bio-Inspired Optimization for Medical Data Mining is a groundbreaking book that delves into the convergence of nature’s ingenious algorithms and cutting-edge healthcare technology. Through a comprehensive exploration of state-of-the-art algorithms and practical case studies, readers gain unparalleled insights into optimizing medical data processing, enabling more precise diagnosis, optimizing treatment plans, and ultimately advancing the field of healthcare. Organized into 15 chapters, readers learn about the theoretical foundation of pragmatic implementation strategies and actionable advice. In addition, it addresses current developments in molecular subtyping and how they can enhance clinical care. By bridging the gap between cutting-edge technology and critical healthcare challenges, this book is a pivotal contribution, providing a roadmap for leveraging nature-inspired algorithms. In this book, the reader will discover Cutting-edge bio-inspired algorithms designed to optimize medical data processing, providing efficient and accurate solutions for complex healthcare challenges; How bio-inspired optimization can fine-tune diagnostic accuracy, leading to better patient outcomes and improved medical decision-making; How bio-inspired optimization propels healthcare into a new era, unlocking transformative solutions for medical data analysis; Practical insights and actionable advice on implementing bio-inspired optimization techniques and equipping effective real-world medical data scenarios; Compelling case studies illustrating how bio-inspired optimization has made a significant impact in the medical field, inspiring similar success stories. Audience This book is designed for a wide-ranging audience, including medical professionals, healthcare researchers, data scientists, and technology enthusiasts.

Bio-Inspired Optimization Techniques in Blockchain Systems

Author: Vignesh, U.

Publisher: IGI Global

Published: 2024-01-29

Total Pages: 306

ISBN-13:

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In the dynamic landscape of bioinformatics and blockchain technology, a profound challenge is evident: ensuring secure exchange and analysis of complex biological data while maintaining data integrity and ownership. Traditional methods fall short in seamlessly transferring genomic data, spurring the fusion of blockchain innovation and optimization algorithms as a groundbreaking solution. Biology-Inspired Optimization Techniques in Blockchain Systems directly addresses the data integrity and ownership dilemma in bioinformatics and blockchain. Despite the intricacies of genomic data, blockchain's potential solution faces obstacles like data volume and slow transactions. These challenges are adeptly overcome through optimization algorithms. The book, authored by experts in bioinformatics, blockchain, and optimization, offers a comprehensive guide, showcasing how blockchain architecture and biological data intricacies can harmonize. It provides a blueprint for using blockchain to store genomic variants and aligned reads. This work empowers developers, data scientists, and researchers to overcome technological barriers, redefining the landscape of bioinformatics and beyond.

Nature-Inspired Optimization Methodologies in Biomedical and Healthcare

Author: Janmenjoy Nayak

Publisher: Springer Nature

Published: 2022-11-14

Total Pages: 304

ISBN-13: 3031175441

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This book introduces a variety of well-proven and newly developed nature-inspired optimization algorithms solving a wide range of real-life biomedical and healthcare problems. Few solo and hybrid approaches are demonstrated in a lucid manner for the effective integration and finding solution for a large-scale complex healthcare problem. In the present bigdata-based computing scenario, nature-inspired optimization techniques present adaptive mechanisms that permit the understanding of complex data and altering environments. This book is a voluminous collection for the confront faced by the healthcare institutions and hospitals for practical analysis, storage, and data analysis. It explores the distinct nature-inspired optimization-based approaches that are able to handle more accurate outcomes for the current biomedical and healthcare problems. In addition to providing a state-of-the-art and advanced intelligent methods, it also enlightens an insight for solving diversified healthcare problems such as cancer and diabetes.

Nature-Inspired Optimization Algorithms

Author: Aditya Khamparia

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2021-02-08

Total Pages: 201

ISBN-13: 311067615X

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This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations

Bio-Inspired Optimization in Fog and Edge Computing Environments

Author: Punit Gupta

Publisher: CRC Press

Published: 2023-01-20

Total Pages: 269

ISBN-13: 1000811514

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A new era of complexity science is emerging, in which nature- and bio-inspired principles are being applied to provide solutions. At the same time, the complexity of systems is increasing due to such models like the Internet of Things (IoT) and fog computing. Will complexity science, applying the principles of nature, be able to tackle the challenges posed by highly complex networked systems? Bio-Inspired Optimization in Fog and Edge Computing: Principles, Algorithms, and Systems is an attempt to answer this question. It presents innovative, bio-inspired solutions for fog and edge computing and highlights the role of machine learning and informatics. Nature- or biological-inspired techniques are successful tools to understand and analyze a collective behavior. As this book demonstrates, algorithms, and mechanisms of self-organization of complex natural systems have been used to solve optimization problems, particularly in complex systems that are adaptive, ever-evolving, and distributed in nature. The chapters look at ways of enhancingto enhance the performance of fog networks in real-world applications using nature-based optimization techniques. They discuss challenges and provide solutions to the concerns of security, privacy, and power consumption in cloud data center nodes and fog computing networks. The book also examines how: The existing fog and edge architecture is used to provide solutions to future challenges. A geographical information system (GIS) can be used with fog computing to help users in an urban region access prime healthcare. An optimization framework helps in cloud resource management. Fog computing can improve the quality, quantity, long-term viability, and cost-effectiveness in agricultural production. Virtualization can support fog computing, increase resources to be allocated, and be applied to different network layers. The combination of fog computing and IoT or cloud computing can help healthcare workers predict and analyze diseases in patients.

Nature-Inspired Optimization Algorithms

Author: Aditya Khamparia

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2021-02-08

Total Pages: 168

ISBN-13: 3110676117

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Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing

Author: Simon James Fong

Publisher: Springer Nature

Published: 2020-08-25

Total Pages: 228

ISBN-13: 981156695X

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This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.

Bio-Inspired Intelligence for Smart Decision-Making

Author: Jaganathan, Ramkumar

Publisher: IGI Global

Published: 2024-05-14

Total Pages: 355

ISBN-13:

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In today's complex and fast-paced world, decision-making is critical to problem-solving across industries and academia. However, traditional optimization techniques often need help to cope with the challenges posed by dynamic and intricate environments. This limitation hampers decision-makers' ability to tackle complex problems and seize opportunities effectively. As such, there is a pressing need for innovative approaches that can enhance decision-making processes, enabling individuals and organizations to navigate uncertainty and achieve optimal outcomes. Bio-Inspired Intelligence for Smart Decision-Making offers a compelling solution to this challenge. By exploring the intersection of bio-inspired optimization techniques and decision-making, this book presents a fresh perspective that can revolutionize decisions. The book introduces readers to powerful bio-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies through a multidisciplinary lens that encompasses computer science, artificial intelligence, optimization, and decision science. These algorithms mimic natural systems' efficiency and adaptability, offering a robust framework for researchers, graduate students, and professionals who are addressing complex decision-making problems in diverse fields.

Intelligent Decision Making Through Bio-Inspired Optimization

Author: Jaganathan, Ramkumar

Publisher: IGI Global

Published: 2024-04-15

Total Pages: 291

ISBN-13:

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Academic scholars, entrenched in the complexities of various domains, face the daunting task of navigating intricate decision-making scenarios. The prevailing need for efficient and effective decision-making tools becomes increasingly apparent as traditional methodologies struggle to keep pace with the demands of modern research and industry. This pivotal issue necessitates a shift, urging scholars to explore unconventional approaches that can transcend disciplinary boundaries and unlock new dimensions of problem-solving. In response to these pressing challenges, Intelligent Decision Making Through Bio-Inspired Optimization emerges as a beacon of ingenuity. This groundbreaking book transcends usual disciplinary boundaries, seamlessly integrating computer science, artificial intelligence, optimization, and decision science. Its multidisciplinary approach addresses the inherent complexities faced by scholars, offering a comprehensive exploration of nature-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies. The book's core mission is to empower academic scholars with the tools to overcome contemporary decision-making hurdles, providing a holistic understanding of these bio-inspired approaches and their potential to revolutionize the scholarly landscape.