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Generative AI in Neurology
This book comprehensively explores the intersection between AI and neurology, focusing on the application of generative models in diagnosing, treating, and managing neurodegenerative diseases. It covers the principles of generative AI and its roles in neuroimaging, biomarker identification, medication development, and tailored treatment options. It examines how advanced AI approaches are leveraged to increase the detection and treatment of neurodegenerative illnesses. The concepts are supported by case studies and examples. Features: Focuses on the emerging field of generative models in neurology. Presents an interdisciplinary approach that bridges AI and medical applications. Examines the ability of neural diffusion models to generate genuine data to enhance healthcare AI. Discusses tools for the adaptation and augmentation of medical images and healthcare data domains. Includes case studies and practical impacts. This book is aimed at graduate students and researchers in biomedical and computer engineering, artificial intelligence, and health informatics.
Artificial Intelligence and Applications
The papers in this book are high quality refereed papers presented at ICAIA 2025, the third International Conference on Artificial Intelligence and Applications, held at Maharaja Surajmal Institute of Technology, New Delhi in March 2025. This book presents new and innovative developments and applications in machine learning, data mining, neural networks, computation optimisation technologies, followed by research applications in signals, language and classification, prediction, recommendations, and systems. This book is essential for researchers and practitioners in this field.
Next Generation Healthcare
Healthcare faces significant challenges due to fragmented data, vendor-locked systems, and security concerns, which hinder the timely delivery of clinical insights and efficient workflow management. This book explores the transformative potential of AI, particularly deep learning (DL) AI, in addressing these issues and enabling personalized healthcare. It covers diverse applications such as clinical trials, telemedicine, EHR management, and disease detection, emphasizing the importance of accurate algorithms to enhance patient outcomes. Key chapters delve into AI’s impact on areas like Parkinson’s and Alzheimer’s detection, the role of blockchain in data integrity, the use of NLP, AR/VR in healthcare, and strategies to combat billing fraud. The book also highlights the importance of diversity in healthcare and presents cutting-edge DL frameworks, such as YOLOv8 and U-Net, for medical image segmentation, offering valuable insights for researchers, practitioners, and policymakers alike.
Feature Fusion for Next-Generation AI
This book delves into the fundamental concepts, methodologies, and practical implementations of feature fusion, providing valuable perspectives on how merging several data aspects might augment the decision-making skills of artificial intelligence. Feature fusion is inherently connected to the advancement of intelligent solutions from medical data as it enables the incorporation of various and complementary data sources to construct more advanced AI models. Within the medical domain, data manifests in diverse formats, including electronic health records (EHRs), medical imaging, genomic data, and real-time sensor metrics. Although each of these data kinds offers distinct perspectives, they ma...
Advancing Cyber Threat Detection Through Quantum and Edge Computing
As cyber threats grow in scale, sophistication, and frequency, traditional detection methods struggle to keep pace. To address this landscape, researchers and organizations turn to emerging technologies like quantum computing and edge computing. Quantum computing offers increased processing power, capable of analyzing complex data patterns and encryptions. Meanwhile, edge computing enables real-time threat detection and increases response times. By combining these two technologies, it creates smarter, faster, and more adaptive cybersecurity systems. Further exploration into how the convergence of quantum and edge computing can revolutionize cyber threat detection may pave the way for more re...
Proceedings of International Conference on Generative AI, Cryptography and Predictive Analytics
The book presents the proceedings of the International Conference on Generative AI, Cryptography and Predictive Analytics (ICGCPA 2024), held at VIPS-TC, School of Engineering and Technology, Pitampura, Delhi, India, during June 28 – 29, 2024. It covers Generative AI's role in problem-solving, examining applications in image synthesis, content creation, healthcare, and optimization challenges. This book is a valuable resource for postgraduate students in various engineering disciplines.
Theory, Practice, and Future Direction of Large Language Models
Large Language Models (LLMs) represent a groundbreaking evolution in the field of artificial intelligence, blending theory, practice, and future potential to reshape industries and human-computer interaction. At the theoretical level, LLMs are rooted in deep learning architectures, which allow them to process and generate natural language with fluency. In practice, they transform sectors like healthcare, education, customer service, and content creation, by automating tasks, providing insights, and enhancing user experiences. However, the use of LLMs also brings challenges, like ethical concerns regarding bias, misinformation, and data privacy, alongside technical issues like computational c...
Secrets of Zynpagua
The Moon Is Calling: Read the Stars! This is a story of a cursed land called Zynpagua. Not many years ago, Zynpagua was a part of the Earth. It was ruled by King Soto and Queen Sussaina. The queen possessed supernatural powers, which she used to bring happiness and prosperity to her people. Zynpagua thus was a very happy land. But an evil eye was watching it. It was the eye of the scientist Drudan. He tricked the king and the queen to ignore their kingdom. This angered the Sun and Stars, and they refused to shower their blessing on Zynpagua. In the meantime, Drudan created a fatal violet light to kill King Soto. The violet light generated catastrophic movements that separated Zynpagua from the Earth, carrying with it all the people on the land. Without the support of the Sun, Zynpagua became a dark planet. Drudan imprisoned Queen Sussaina behind the shadow of the moon, while King Soto could not be traced. Zynpagua became a cursed land. While in prison, Queen Sussaina secretly gives birth to a girl and transfers all her powers to her and sends her to the Earth. Now the only solution to Zynpaguas misery is the return of this princess.
Automating Software Defect Detection Through Machine Learning and LLMs
As software systems grow in complexity and scale, ensuring their reliability and quality becomes challenging. Traditional methods of defect detection are time-consuming, prone to errors, and inadequate for identifying issues. To address these limitations, the integration of machine learning (ML) techniques and large language models (LLMs) emerges as a transformative approach in automating software defect detection. ML algorithms can learn from historical bug data to predict vulnerabilities, while LLMs can detect anomalies with high accuracy. This convergence holds the potential to improve automation, software engineering, and defect detection, while introducing new challenges in interpretabi...
