Artificial Intelligence In Acute Neurology
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Artificial Intelligence in Acute Neurology
In recent years, the intersection of artificial intelligence (AI) and neurology has led to extraordinary advancements in the diagnosis, treatment, and management of acute neurological conditions. AI-driven technologies, such as machine learning algorithms and deep neural networks, have shown immense promise in transforming the landscape of acute care for patients facing neurological emergencies. This special issue aims to provide a comprehensive platform for researchers to showcase their cutting-edge work and explore the transformative potential of AI in acute neurology. The goal of this Research Topic is to shed light on the remarkable strides made in AI applications within acute neurology and emphasize their critical role in addressing existing gaps in patient care. As we move towards an era of personalized medicine, AI-based tools have the potential to revolutionize early detection, diagnosis, and treatment decision-making in acute neurological scenarios. By sharing your novel findings and perspectives, you will contribute to bridging the gap between AI research and clinical practice, fostering evidence-based approaches to improve patient outcomes.
Artificial Intelligence in Neurological Disorders
Author: Rishabha Malviya
language: en
Publisher: John Wiley & Sons
Release Date: 2025-08-04
The book gives invaluable insights into how artificial intelligence is revolutionizing the management and treatment of neurological disorders, empowering you to stay ahead in the rapidly evolving landscape of healthcare. Embark on a groundbreaking exploration of the intersection between cutting-edge technology and the intricate complexities of neurological disorders. Artificial Intelligence in Neurological Disorders: Management, Diagnosis and Treatment comprehensively introduces how artificial intelligence is becoming a vital ally in neurology, offering unprecedented advancements in management, diagnosis, and treatment. As the digital age converges with medical expertise, this book unveils a comprehensive roadmap for leveraging artificial intelligence to revolutionize neurological healthcare. Delve into the core principles that underpin AI applications in the field by exploring intricate algorithms that enhance the precision of diagnosis and how machine learning not only refines the understanding of neurological disorders but also paves the way for personalized treatment strategies tailored to individual patient needs. With compelling case studies and real-world examples, the realms of neuroscience and artificial intelligence converge, illustrating the symbiotic relationship that holds the promise of transforming patient care. Readers of this book will find it: Provides future perspectives on advancing artificial intelligence applications in neurological disorders; Focuses on the role of AI in diagnostics, delving into how advanced algorithms and machine learning techniques contribute to more accurate and timely diagnosis of neurological disorders; Emphasizes practical integration of AI tools into clinical practice, offering insights into how healthcare professionals can leverage AI technology for more effective patient care; Recognizes the interdisciplinary nature of neurology and AI, bridging the gap between these fields, making it accessible to healthcare professionals, researchers, and technologists; Addresses the ethical implications of AI in healthcare, exploring issues such as data privacy, bias, and the responsible deployment of AI technologies in the neurological domain. Audience Researchers, scientists, industrialists, faculty members, healthcare professionals, hospital management, biomedical industrialists, engineers, and IT professionals interested in studying the intersection of AI and neurology.
Artificial Intelligence in Healthcare
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data