Yugal Kumar – författare

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics.

In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data.

This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.

Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems. Includes several privacy preservation techniques for medical data. Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis. Offers case studies and applications relating to machine learning, big data, and health care analysis.

Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data addresses the urgent need for innovation in today’s complex healthcare data landscape, characterized by pandemics, aging populations, and escalating chronic conditions. This book introduces the concept of ‘Healthcare 5.0’ as an interconnected, data-driven, and patient-centric framework, where advanced technologies-such as AI, ML, IoMT, Big Data, and Large Language Models (LLMs)-converge to optimize care, streamline operations, and deliver personalized, predictive solutions that meet real-world challenges. Comprising six comprehensive sections, the book moves from core AI applications in electronic health records, drug discovery, data management, and privacy, through cutting-edge big data analytics for precise disease forecasting and diagnosis. It explores new research advances in the Internet of Medical Things including connected device architectures and their fusion with AI for dynamic decision-making. The third section focuses on data analytics in telemedicine, remote care, system usability, and integration in Healthcare 5.0. The personalized healthcare section details analysis and applications in AI- and IoT-powered assistance, and real-time monitoring. The last section explores the development of LLMs and their applications in medical imaging, clinical decision support, predictive analytics, system architectures, as well as the ethical challenges of their deployment in healthcare. Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data serves as an essential resource for graduate students, researchers, and engineers in computer science, data science, and biomedical informatics. It bridges theory and practical application, offering interdisciplinary insights, foundational background, detailed case studies, and guidance on navigating the next generation of healthcare data systems. Whether for research or real-world innovation, readers gain the tools to design, analyze, and implement intelligent healthcare data solutions for a rapidly evolving digital era.Delivers practical frameworks for integrating AI, ML, Big Data, and IoMT into modern healthcare data systemsExplores predictive data analytics for improved patient outcomes in personalized medicineExamines implementation challenges, data management, and security solutions for healthcare technology adoptionHighlights advancements in data architecture for telemedicine and remote care, enhancing accessibility and efficiency

This book focuses mainly on the usages of three key technologies: IoT, big data, and AI for various day to day applications.

This book focuses mainly on the usages of three key technologies: IoT, big data, and AI for various day to day applications.

This book constitutes the refereed proceedings of the First International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2018, held in Solan, India, in February 2018.The 37 revised full papers presented were carefully reviewed and selected from 239 submissions. The prime aim of the conference is to invite researchers from different domains of network and communication technologies to a single platform to showcase their research ideas. The selected papers are organized in topical sections on communication technologies, Internet of Things (IoT), network technologies, and wireless networks.

This book constitutes the refereed proceedings of the Second International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2019, held in Chandigarh, India, in November 2019. The 49 revised full papers and 6 short papers presented were carefully reviewed and selected from 226 submissions.

This two-wolume set (CCIS 1395-1396) constitutes the refereed proceedings of the Third International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020, held in Taganrog, Russia, in October 2020.The 80 revised full papers presented were carefully reviewed and selected from 291 submissions.

This two-wolume set (CCIS 1395-1396) constitutes the refereed proceedings of the Third International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020, held in Taganrog, Russia, in October 2020.The 80 revised papers presented were carefully reviewed and selected from 291 submissions.