Bipin Kumar Rai – författare

The objective of the book is to use advanced deep learning techniques to unlock the complexities of genomic data. It reveals hidden and unknown patterns, to improve our understanding the role of genetics in diseases, speeding up drug discovery processes, illuminating evolutionary trajectories, and dealing with the challenges posed by large genomic datasets. It also addresses ethical concerns, provides real-world applications, reviews future frontiers like as quantum computing and multi-omics integration, and presents a thorough picture of the genetic environment. Overall, the book aims to enhance our ability to use genomics for more precise forecasts, personalised therapies, and a better understanding of the underlying genetic fabric that defines life.

The objective of the book is to use advanced deep learning techniques to unlock the complexities of genomic data. It reveals hidden and unknown patterns, to improve our understanding the role of genetics in diseases, speeding up drug discovery processes, illuminating evolutionary trajectories, and dealing with the challenges posed by large genomic datasets. It also addresses ethical concerns, provides real-world applications, reviews future frontiers like as quantum computing and multi-omics integration, and presents a thorough picture of the genetic environment. Overall, the book aims to enhance our ability to use genomics for more precise forecasts, personalised therapies, and a better understanding of the underlying genetic fabric that defines life.

The objective of the book is to use advanced deep learning techniques to unlock the complexities of genomic data. It reveals hidden and unknown patterns, to improve our understanding the role of genetics in diseases, speeding up drug discovery processes, illuminating evolutionary trajectories, and dealing with the challenges posed by large genomic datasets. It also addresses ethical concerns, provides real-world applications, reviews future frontiers like as quantum computing and multi-omics integration, and presents a thorough picture of the genetic environment. Overall, the book aims to enhance our ability to use genomics for more precise forecasts, personalised therapies, and a better understanding of the underlying genetic fabric that defines life.

Advanced computational techniques and intelligent algorithms are now being used for processing, analyzing, and interpreting medical images across diverse healthcare applications. It integrates image processing, machine learning, deep learning, and computer vision to enhance diagnostic accuracy, disease detection, and clinical decision-making. Its potential lies in enabling faster, automated, and more precise medical assessments while supporting personalized and data-driven healthcare systems. The field also drives innovation in radiology, telemedicine, surgical planning, and smart healthcare technologies, making it a critical area of modern biomedical research and practice.The book delves into the latest computational methodologies and artificial intelligence techniques used in the analysis, interpretation, and enhancement of digital medical images. It aims to cover a wide array of topics, from foundational imaging techniques to advanced Al-driven models, including machine learning, deep learning, and neural networks applied in medical imaging. It also addresses critical aspects such as data preprocessing, feature extraction, segmentation, and diagnostic interpretation, offering insights into how computational applies are revolutionizing clinical decision-making, diagnostic accuracy, and patient outcomes.This book is designed for researchers and professionals in medical imaging, artificial intelligence, biomedical engineering, and healthcare. It is also useful for clinicians and industry practitioners applying computational techniques to improve diagnostic decision-making.

Master the future of secure technology with this essential guide, which delivers a practical, forward-looking blueprint for combining AI, blockchain, and advanced cryptography to build powerful, decentralized systems without compromising data privacy. As AI systems grow more powerful and data more valuable, the tension between collaborative intelligence and individual privacy has never been more urgent. This book confronts this challenge head-on, offering a comprehensive and forward-looking exploration of how federated learning, blockchain technology, and advanced cryptographic techniques can be combined to build AI systems that are powerful and trustworthy. From foundational concepts in distributed machine learning and data sovereignty to cutting-edge topics such as zero-knowledge proofs, homomorphic encryption, and quantum-resistant privacy solutions, this book is structured to serve both learners and practitioners. The book moves deliberately from theory to practice, establishing core principles before tackling complex architectures, consensus mechanisms, smart contract governance, and incentive models that make decentralized AI networks viable at scale. Real-world applications anchor the technical content throughout, with dedicated chapters examining privacy-preserving fraud detection in finance, blockchain-AI collaboration in healthcare, and intelligent infrastructure in smart cities and IoT ecosystems. Supported by case studies, architectural diagrams, and practical guidance on tools, it is an essential resource for anyone working at the intersection of AI, blockchain, and data privacy to shape the secure, decentralized intelligent systems of tomorrow. Master the future of secure technology with this essential guide, which delivers a practical, forward-looking blueprint for combining AI, blockchain, and advanced cryptography to build powerful, decentralized systems without compromising data privacy.

This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, dueto the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs).

This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, dueto the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs).