دانلود کتاب یادگیری عمیق در نقشه‌برداری ژنوم، محاسبات و تحلیل

The rapid evolution of deep learning has opened transformative avenues in genome mapping, computation, and medical data analysis. This book, Deep Learning in Genome Mapping: Computation and Analysis, is designed to provide a comprehensive yet accessible exploration of how artificial intelligence and optimization techniques are revolutionizing genomic science and healthcare applications. The chapters in this volume are carefully curated to cover both foundational and advanced perspectives. Beginning with computational strategies and optimization algorithms for genome mapping, readers are introduced to the role of deep learning in addressing the complexity of large-scale biological data. Topics such as multi-objective evolutionary algorithms and deep learning–driven medical data engineering illustrate how diverse approaches converge to enhance accuracy and knowledge discovery in genomic studies. The text also bridges methodological insights with real-world applications. Techniques integrating neural networks, image processing, and edge detection are presented alongside applications in smart healthcare and medical imaging. The inclusion of chapters on noise reduction strategies, AI-based heart delineation in chest X-rays, and innovations in medical science highlights the book’s interdisciplinary scope—linking genomics, imaging, and machine learning for practical impact. While the focus remains on genome mapping, the broader context of healthcare and medical data analysis is deliberately incorporated. This ensures that the book speaks to a wide audience, including computer scientists, biomedical engineers, healthcare researchers, and students eager to understand the intersection of artificial intelligence with life sciences. The contributors to this volume are experts who bring clarity to complex topics, balancing theoretical foundations with practical implementations. It is our hope that this book not only deepens the reader’s understanding of deep learning in genome mapping but also inspires further research and innovation in this rapidly advancing field. We extend our gratitude to the researchers, practitioners, and academicians whose contributions make this volume a valuable resource. May it serve as both a guide and a stimulus for advancing intelligent solutions in genomics and healthcare.