Ai Model Design And Data Management For Disease Prediction
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AI Model Design and Data Management for Disease Prediction
Author: Muniasamy, Anandhavalli
language: en
Publisher: IGI Global
Release Date: 2025-07-09
The design of artificial intelligence (AI) models for disease prediction advances fields that combine medical expertise, data science, and computational power to improve diagnostic accuracy and patient outcomes. The design of predictive models is central to this process, tailored to analyze complex healthcare data. Effective data management in healthcare involves the collection, integration, and storage of high-quality clinical and biomedical datasets. Ensuring data privacy and addressing biases are challenges that must be navigated to develop reliable and ethical AI systems. Thoughtful model design and effective data management strategies may ensure earlier detection, personalized treatment, and better resource allocation in modern healthcare systems. AI Model Design and Data Management for Disease Prediction explores the integration of intelligent technologies into medical prediction and diagnosis. It examines the usage of AI for enhanced healthcare data management. This book covers topics such as data science, medical imaging, and prediction models, and is a useful resource for computer engineers, medical professionals, academicians, researchers, and data scientists.
AI Model Design and Data Management for Disease Prediction
Author: Anandhavalli Muniasamy
language: en
Publisher: Medical Information Science Reference
Release Date: 2025-07-04
The design of artificial intelligence (AI) models for disease prediction advances fields that combine medical expertise, data science, and computational power to improve diagnostic accuracy and patient outcomes. The design of predictive models is central to this process, tailored to analyze complex healthcare data. Effective data management in healthcare involves the collection, integration, and storage of high-quality clinical and biomedical datasets. Ensuring data privacy and addressing biases are challenges that must be navigated to develop reliable and ethical AI systems. Thoughtful model design and effective data management strategies may ensure earlier detection, personalized treatment, and better resource allocation in modern healthcare systems. AI Model Design and Data Management for Disease Prediction explores the integration of intelligent technologies into medical prediction and diagnosis. It examines the usage of AI for enhanced healthcare data management. This book covers topics such as data science, medical imaging, and prediction models, and is a useful resource for computer engineers, medical professionals, academicians, researchers, and data scientists.
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