Extracting Insights From Digital Public Health Data Using Artificial Intelligence


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Extracting Insights from Digital Public Health Data using Artificial Intelligence


Extracting Insights from Digital Public Health Data using Artificial Intelligence

Author: Yu-Dong Zhang

language: en

Publisher: Frontiers Media SA

Release Date: 2022-12-05


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Extracting Insights from Digital Public Health Data using Artificial Intelligence, volume II


Extracting Insights from Digital Public Health Data using Artificial Intelligence, volume II

Author: Steven Fernandes

language: en

Publisher: Frontiers Media SA

Release Date: 2024-04-19


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This Research Topic is a follow on from the Topic Editors' successful volume I. Artificial Intelligence (AI) has the ability to perform automated/case-based reasoning, constraint processing, deep learning, and deep reinforcement learning. Recent advancements in AI techniques and GPU (graphics processing unit) computing capabilities have made it possible to process large volumes of data and extract valuable insights within a short period. Digital public health data are enormous, and harnessing AI's power can lead to exciting and ground-breaking research. Due to the current COVID-19 pandemic, AI can assist in disease surveillance methods, infectious disease modeling, non-contact temperature screening, intelligent contact tracking, detecting social/economic factors on transmission, effective health communication and misinformation detection, identifying factors that affect the mental and emotional health of the public.

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