Shailaja Patil - Böcker

This reference text introduces the classical probabilistic model, deep learning, and big data techniques for improving medical imaging and detecting various diseases.The text addresses a wide variety of application areas in medical imaging where deep learning techniques provide solutions with lesser human intervention and reduced time. It comprehensively covers important machine learning for signal analysis, deep learning techniques for cancer detection, diabetic cases, skin image analysis, Alzheimer’s disease detection, coronary disease detection, medical image forensic, fetal anomaly detection, and plant phytology. The text will serve as a useful text for graduate students and academic researchers in the fields of electronics engineering, computer science, biomedical engineering, and electrical engineering.

This reference text introduces the classical probabilistic model, deep learning, and big data techniques for improving medical imaging and detecting various diseases.The text addresses a wide variety of application areas in medical imaging where deep learning techniques provide solutions with lesser human intervention and reduced time. It comprehensively covers important machine learning for signal analysis, deep learning techniques for cancer detection, diabetic cases, skin image analysis, Alzheimer’s disease detection, coronary disease detection, medical image forensic, fetal anomaly detection, and plant phytology. The text will serve as a useful text for graduate students and academic researchers in the fields of electronics engineering, computer science, biomedical engineering, and electrical engineering.

Large language models (LLMs) represent a profound breakthrough in artificial intelligence. More than just statistical tools, these vast neural networks undergo an intensive training process that unlocks unexpected, emergent abilities. Models like ChatGPT are now demonstrating a surprising grasp of reasoning, semantics, and real-world concepts, leading many researchers to ask: are we witnessing the first sparks of Artificial General Intelligence (AGI)?These models are doing more than just revolutionizing natural language processing; they are forcing us to reconsider the boundaries of machine intelligence. While their applications in chatbots, complex problem-solving, and content creation are already reshaping our digital world, their deeper implications point toward an entirely new era of AI.To understand these emergent capabilities and confront the AGI question, a deep dive into the core technology is essential. This co-authored book provides that crucial foundation. The authors explore the significance and capabilities of LLMs, alongside the immense ethical, social, and security challenges that arise as these models grow more powerful.For anyone seeking a comprehensive guide to navigate this new territory, The Power of Large Language Models and AI in the Digital Age: Technologies, applications, security and ethics is a valuable resource. It is essential reading for data scientists, researchers from academia and industry, lecturers, and advanced students in AI, computer science, and data science who will shape the future of intelligent systems.