Bio Inspired Algorithms In Machine Learning And Deep Learning For Disease Detection
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Bio Inspired Algorithms In Machine Learning And Deep Learning For Disease Detection
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Author : Balasubramaniam S
language : en
Publisher: CRC Press
Release Date : 2025-03-13
Bio Inspired Algorithms In Machine Learning And Deep Learning For Disease Detection written by Balasubramaniam S and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Technology & Engineering categories.
Currently, computational intelligence approaches are utilised in various science and engineering applications to analyse information, make decisions, and achieve optimisation goals. Over the past few decades, various techniques and algorithms have been created in disciplines such as genetic algorithms, artificial neural networks, evolutionary algorithms, and fuzzy algorithms. In the coming years, intelligent optimisation algorithms are anticipated to become more efficient in addressing various issues in engineering, scientific, medical, space, and artificial satellite fields, particularly in early disease diagnosis. A metaheuristic in computer science is designed to discover optimisation algorithms capable of solving intricate issues. Metaheuristics are optimisation algorithms that mimic biological behaviours of animals or birds and are utilised to discover the best solution for a certain problem. A meta-heuristic is an advanced approach used by heuristics to tackle intricate optimisation problems. A metaheuristic in mathematical programming is a method that seeks a solution to an optimisation problem. Metaheuristics utilise a heuristic function to assist in the search process. Heuristic search can be categorised as blind search or informed search. Meta-heuristic optimisation algorithms are gaining popularity in various applications due to their simplicity, independence from data trends, ability to find optimal solutions, and versatility across different fields. Recently, many nature-inspired computation algorithms have been utilised to diagnose people with different diseases. Nature-inspired methodologies are now widely utilised across several fields for tasks such as data analysis, decision-making, and optimisation. Techniques inspired by nature are categorised as either biology-based or natural phenomena-based. Bioinspired computing encompasses various topics in computer science, mathematics, and biology in recent years. Bio-inspired computer optimisation algorithms are a developing method that utilises concepts and inspiration from biological development to create new and resilient competitive strategies. Bio-inspired optimisation algorithms have gained recognition in machine learning and deep learning for solving complicated issues in science and engineering. Utilising BIAs learning methods with machine learning and deep learning shows great promise for accurately classifying medical conditions. This book explores the historical development of bio-inspired algorithms and their application in machine learning and deep learning models for disease diagnosis, including COVID-19, heart diseases, cancer, diabetes and some other diseases. It discusses the advantages of using bio-inspired algorithms in disease diagnosis and concludes with research directions and future prospects in this field.
Bio Inspired Neurocomputing
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Author : Akash Kumar Bhoi
language : en
Publisher: Springer Nature
Release Date : 2020-07-21
Bio Inspired Neurocomputing written by Akash Kumar Bhoi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-21 with Technology & Engineering categories.
This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.
Bio Inspired Algorithms And Devices For Treatment Of Cognitive Diseases Using Future Technologies
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Author : Gupta, Shweta
language : en
Publisher: IGI Global
Release Date : 2022-02-11
Bio Inspired Algorithms And Devices For Treatment Of Cognitive Diseases Using Future Technologies written by Gupta, Shweta and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-11 with Technology & Engineering categories.
As there are no proper medical tests available to predict certain diseases such as Alzheimer’s and Parkinson’s at an early stage, there is a need to further study and consider the potential uses of bio- and nature-inspired algorithms and future technologies such as machine learning in correlation to disease detection and treatment. Bio-Inspired Algorithms and Devices for Treatment of Cognitive Diseases Using Future Technologies considers new tools for early detection of cognitive brain diseases using devices and algorithms whose basic concept is taken from nature and discusses design, analysis, and application of various bionics or bio-inspired algorithms. Covering topics such as depression and cognitive science, this publication is an ideal resource for researchers, academicians, industry professionals, psychologists, psychiatrists, nurses, engineers, instructors, and students.
Bio Inspired Computing
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Author : Anu Bajaj
language : en
Publisher: Springer Nature
Release Date : 2025-06-05
Bio Inspired Computing written by Anu Bajaj and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-05 with Computers categories.
This book presents 53 selected papers focused on Deep Learning and Large Language Models from the 14th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2023) and 13th World Congress on Information and Communication Technologies (WICT 2023), which was held in five different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India and in online mode. The 23rd International Conference on Hybrid Intelligent Systems (IBICA-WICT 2023) was focusing on synergistic combinations of multiple approaches to develop the next generation of bio-inspired computing and ICT systems. IBICA-WICT 2023 had contributions by authors from 36 countries. This book offers a valuable reference guide for all scientists, academicians, researchers, students, and practitioners focused on advanced machine learning including deep learning methods, large language models, and its real-world applications.
Computational Vision And Bio Inspired Computing
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Author : S. Smys
language : en
Publisher: Springer Nature
Release Date : 2020-01-06
Computational Vision And Bio Inspired Computing written by S. Smys and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-06 with Technology & Engineering categories.
This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. Due to the rapid advances in the emerging information, communication and computing technologies, the Internet of Things, cloud and edge computing, and artificial intelligence play a significant role in the computational vision context. In recent years, computational vision has contributed to enhancing the methods of controlling the operations in biological systems, like ant colony optimization, neural networks, and immune systems. Moreover, the ability of computational vision to process a large number of data streams by implementing new computing paradigms has been demonstrated in numerous studies incorporating computational techniques in the emerging bio-inspired models. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization, and big data modeling and management, that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems, and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.
Advances In Computational Intelligence For Health Informatics And Computer Aided Diagnosis
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Author : A. Malini
language : en
Publisher: CRC Press
Release Date : 2025-04-23
Advances In Computational Intelligence For Health Informatics And Computer Aided Diagnosis written by A. Malini and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-23 with Medical categories.
This book provides a comprehensive overview of the intersection of computational intelligence, health informatics, and computer-aided diagnosis (CAD). The book explores and highlights the latest advancements, methodologies, applications, and tools in these fields. Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools covers a broad spectrum of computational intelligence approaches, from basic concepts to advanced methodologies. The focus on health informatics reflects the book's commitment to researching data integration, privacy issues, and interoperability issues that are crucial in today's healthcare landscape. The book's core is its in-depth examination of CAD systems, which encompasses numerous healthcare sectors and underlines the technological complexity involved in building accurate and efficient diagnostic tools. Some of the other key areas covered include: medical imaging analysis, disease identification and diagnosis, and drug research and development. It also provides case studies that demonstrate how computational intelligence methods are applied in real-world healthcare scenarios, giving readers a practical understanding of the subject matter. The authors then discuss future trends and directions in computational intelligence for health informatics. The book is designed to serve as a guide to for academics, professionals, and students who are curious about the challenges of integrating contemporary computational approaches into medical diagnostics and decision support.
Ai Model Design And Data Management For Disease Prediction
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Author : Muniasamy, Anandhavalli
language : en
Publisher: IGI Global
Release Date : 2025-07-09
Ai Model Design And Data Management For Disease Prediction written by Muniasamy, Anandhavalli and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-09 with Medical categories.
The design of artificial intelligence (AI) models for disease prediction advances fields that combine medical expertise, data science, and computational power to improve diagnostic accuracy and patient outcomes. The design of predictive models is central to this process, tailored to analyze complex healthcare data. Effective data management in healthcare involves the collection, integration, and storage of high-quality clinical and biomedical datasets. Ensuring data privacy and addressing biases are challenges that must be navigated to develop reliable and ethical AI systems. Thoughtful model design and effective data management strategies may ensure earlier detection, personalized treatment, and better resource allocation in modern healthcare systems. AI Model Design and Data Management for Disease Prediction explores the integration of intelligent technologies into medical prediction and diagnosis. It examines the usage of AI for enhanced healthcare data management. This book covers topics such as data science, medical imaging, and prediction models, and is a useful resource for computer engineers, medical professionals, academicians, researchers, and data scientists.
Innovations In Bio Inspired Computing And Applications
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Author : Ajith Abraham
language : en
Publisher: Springer Nature
Release Date : 2022-02-21
Innovations In Bio Inspired Computing And Applications written by Ajith Abraham and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-21 with Technology & Engineering categories.
This book highlights recent research on bio-inspired computing and its various innovative applications in information and communication technologies. It presents 80 high-quality papers from the 12th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2021) and 11th World Congress on Information and Communication Technologies (WICT 2021), which was held online during December 16–18, 2021. As a premier conference, IBICA–WICT brings together researchers, engineers and practitioners whose work involves bio-inspired computing, computational intelligence and their applications in information security, real-world contexts, etc. Including contributions by authors from 25 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Cybernetics Human Cognition And Machine Learning In Communicative Applications
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2025-01-09
Cybernetics Human Cognition And Machine Learning In Communicative Applications written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-09 with Computers categories.
This book presents the fascinating intersection of human cognition and artificial intelligence. Written by leading experts in the fields of cybernetics, cognitive science, and machine learning, this book seeks to bridge the gap between these disciplines and explores the synergies that emerge when humans and machines work together. The book examines the challenges posed by biased data, lack of transparency, and the "black box" nature of some machine learning algorithms. It proposes novel ways to address these issues and foster greater trust and accountability in AI systems. Drawing on cutting-edge research and real-world case studies, it presents a comprehensive and forward-looking perspective on the future of AI and its impact on society. In conclusion, this book offers a compelling exploration of the synergy between human cognition and machine learning, providing insights that are relevant to scholars, researchers, policymakers, and anyone interested in the transformative potential of artificial intelligence.
Recent Advances In Sciences Engineering Information Technology Management
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Author : Dinesh Goyal
language : en
Publisher: CRC Press
Release Date : 2025-02-14
Recent Advances In Sciences Engineering Information Technology Management written by Dinesh Goyal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-14 with Technology & Engineering categories.
This conference covered various interdisciplinary areas such as applied science, physics, material science, and engineering. The audience got a chance to encircle the various interdisciplinary areas and people working on recent technologies in science, engineering, information technology and management. It was based on the theme of converging interdisciplinary topics into a single platform, which helped the participants to think beyond their area and increase their canvas of research.