Multimodal Data Fusion For Bioinformatics Artificial Intelligence
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Multimodal Data Fusion for Bioinformatics Artificial Intelligence
Author: Umesh Kumar Lilhore
language: en
Publisher: John Wiley & Sons
Release Date: 2025-01-14
Multimodal Data Fusion for Bioinformatics Artificial Intelligence is a must-have for anyone interested in the intersection of AI and bioinformatics, as it delves into innovative data fusion methods and their applications in ‘omics’ research while addressing the ethical implications and future developments shaping the field today. Multimodal Data Fusion for Bioinformatics Artificial Intelligence is an indispensable resource for those exploring how cutting-edge data fusion methods interact with the rapidly developing field of bioinformatics. Beginning with the basics of integrating different data types, this book delves into the use of AI for processing and understanding complex “omics” data, ranging from genomics to metabolomics. The revolutionary potential of AI techniques in bioinformatics is thoroughly explored, including the use of neural networks, graph-based algorithms, single-cell RNA sequencing, and other cutting-edge topics. The second half of the book focuses on the ethical and practical implications of using AI in bioinformatics. The tangible benefits of these technologies in healthcare and research are highlighted in chapters devoted to precision medicine, drug development, and biomedical literature. The book addresses a wide range of ethical concerns, from data privacy to model interpretability, providing readers with a well-rounded education on the subject. Finally, the book explores forward-looking developments such as quantum computing and augmented reality in bioinformatics AI. This comprehensive resource offers a bird’s-eye view of the intersection of AI, data fusion, and bioinformatics, catering to readers of all experience levels.
Multimodal Data Fusion for Bioinformatics Artificial Intelligence
Author: Umesh Kumar Lilhore
language: en
Publisher: John Wiley & Sons
Release Date: 2025-03-05
Multimodal Data Fusion for Bioinformatics Artificial Intelligence is a must-have for anyone interested in the intersection of AI and bioinformatics, as it delves into innovative data fusion methods and their applications in ‘omics’ research while addressing the ethical implications and future developments shaping the field today. Multimodal Data Fusion for Bioinformatics Artificial Intelligence is an indispensable resource for those exploring how cutting-edge data fusion methods interact with the rapidly developing field of bioinformatics. Beginning with the basics of integrating different data types, this book delves into the use of AI for processing and understanding complex “omics” data, ranging from genomics to metabolomics. The revolutionary potential of AI techniques in bioinformatics is thoroughly explored, including the use of neural networks, graph-based algorithms, single-cell RNA sequencing, and other cutting-edge topics. The second half of the book focuses on the ethical and practical implications of using AI in bioinformatics. The tangible benefits of these technologies in healthcare and research are highlighted in chapters devoted to precision medicine, drug development, and biomedical literature. The book addresses a wide range of ethical concerns, from data privacy to model interpretability, providing readers with a well-rounded education on the subject. Finally, the book explores forward-looking developments such as quantum computing and augmented reality in bioinformatics AI. This comprehensive resource offers a bird’s-eye view of the intersection of AI, data fusion, and bioinformatics, catering to readers of all experience levels.
Integrating Neurocomputing with Artificial Intelligence
Integrating Neurocomputing with Artificial Intelligence provides unparalleled insights into the cutting-edge convergence of neuroscience and computing, enriched with real-world case studies and expert analyses that harness the transformative potential of neurocomputing in various disciplines. Integrating Neurocomputing with Artificial Intelligence is a comprehensive volume that delves into the forefront of the neurocomputing landscape, offering a rich tapestry of insights and cutting-edge innovations. This volume unfolds as a carefully curated collection of research, showcasing multidimensional perspectives on the intersection of neuroscience and computing. Readers can expect a deep exploration of fundamental theories, methodologies, and breakthrough applications that span the spectrum of neurocomputing. Throughout the book, readers will find a wealth of case studies and real-world examples that exemplify how neurocomputing is being harnessed to address complex challenges across different disciplines. Experts and researchers in the field contribute their expertise, presenting in-depth analyses, empirical findings, and forward-looking projections. Integrating Neurocomputing with Artificial Intelligence serves as a gateway to this fascinating domain, offering a comprehensive exploration of neurocomputing’s foundations, contemporary developments, ethical considerations, and future trajectories. It embodies a collective endeavor to drive progress and unlock the potential of neurocomputing, setting the stage for a future where artificial intelligence is not merely artificial, but profoundly inspired by the elegance and efficiency of the human brain.