Artificial Intelligence Enabled Security For Healthcare Systems


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Artificial Intelligence-Enabled Security for Healthcare Systems


Artificial Intelligence-Enabled Security for Healthcare Systems

Author: Sunil Gupta

language: en

Publisher: Springer Nature

Release Date: 2025-03-01


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The book "AI-Enabled Healthcare Security: Safeguarding Patient Data and Improving Outcomes" focuses on the role of artificial intelligence in enhancing healthcare security and improving patient outcomes. It covers the challenges and risks associated with cybersecurity threats in the healthcare industry and explores the use of AI-based cybersecurity solutions, machine learning algorithms, and predictive analytics to mitigate those risks. The book is intended for healthcare professionals, cybersecurity experts, AI practitioners, and anyone interested in the intersection of healthcare, cybersecurity, and AI. It also highlights emerging technologies and future trends in AI and healthcare security.

Smart Healthcare Systems


Smart Healthcare Systems

Author: Adwitiya Sinha

language: en

Publisher: Chapman & Hall/CRC

Release Date: 2019


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About the Book The book provides details of applying intelligent mining techniques for extracting & pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis & Treatment options Applications of Big Data & Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare & analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions. ng in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare & analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.

Artificial Intelligence in Healthcare


Artificial Intelligence in Healthcare

Author: Adam Bohr

language: en

Publisher: Academic Press

Release Date: 2020-06-21


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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