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Artificial intelligence in healthcare. An analysis of the link of AI to health promotion and prevention programs to face and early-detect non-communicable diseases

2019-06-24 Health & Fitness
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Release : 2019-06-24
Genre : Health & Fitness
Kind : eBook
Book Rating : 86X/5 ( reviews)

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Book Synopsis Artificial intelligence in healthcare. An analysis of the link of AI to health promotion and prevention programs to face and early-detect non-communicable diseases by : Julius Holaus

Download or read book Artificial intelligence in healthcare. An analysis of the link of AI to health promotion and prevention programs to face and early-detect non-communicable diseases written by Julius Holaus. This book was released on 2019-06-24. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2019 in the subject Health - Miscellaneous, grade: 2,00, Management Center Innsbruck, language: English, abstract: The global challenge against non-communicable diseases gained transnational attention over the last years. Statistics illustrate, that approximately 70% of all deaths worldwide can be traced back to chronic diseases. On the other hand, artificial intelligence is on the rise as the number of implemented software featuring machine-learning skills increased tremendously in the last years. Therefore, the purpose of this literature review is to combine those aspects in order to create synergies of the link between existing approaches with the aim to face non-communicable diseases and artificial intelligence. The review focusses firstly specifically only on the most prevalent NCDs and their characteristics before analysing the rise of machine-learning software from the very beginning. In a next step, those two fields will be combined with the aim to point out both benefits and risks when implementing AI in the healthcare sector. The outcome was, that the use of such software would definitely cut a three-digit number of billions of Euros of spending on healthcare due to the possibility to early-detect diseases and the hereby arising possibility to treat patients in a more efficient way as until now. On the other hand, the biggest risk will be, that artificial intelligence works on huge datasets that need to be set up first – during the setting up process of such data, failures can take place which would have a grave impact on further use.

Artificial Intelligence and Machine Learning in Public Healthcare

2022-01-01 Technology & Engineering
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Release : 2022-01-01
Genre : Technology & Engineering
Kind : eBook
Book Rating : 683/5 ( reviews)

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Book Synopsis Artificial Intelligence and Machine Learning in Public Healthcare by : KC Santosh

Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh. This book was released on 2022-01-01. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Artificial Intelligence in Healthcare

2020-06-21 Computers
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Release : 2020-06-21
Genre : Computers
Kind : eBook
Book Rating : 396/5 ( reviews)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr. This book was released on 2020-06-21. Available in PDF, EPUB and Kindle. Book excerpt: 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

Artificial Intelligence and Machine Learning in Public Healthcare

2021
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Release : 2021
Genre :
Kind : eBook
Book Rating : 695/5 ( reviews)

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Book Synopsis Artificial Intelligence and Machine Learning in Public Healthcare by : KC Santosh

Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example-a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Tracking and Preventing Diseases with Artificial Intelligence

2021 Artificial intelligence
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Author :
Release : 2021
Genre : Artificial intelligence
Kind : eBook
Book Rating : 329/5 ( reviews)

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Book Synopsis Tracking and Preventing Diseases with Artificial Intelligence by : Mayuri Mehta

Download or read book Tracking and Preventing Diseases with Artificial Intelligence written by Mayuri Mehta. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of how machine learning and data mining techniques are used for tracking and preventing diseases. It covers several aspects such as stress level identification of a person from his/her speech, automatic diagnosis of disease from X-ray images, intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells, information retrieval from electronic medical record using named entity recognition approaches, and prediction of drug-target interactions. The book is suitable for computer scientists having a bachelor degree in computer science. The book is an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care. Researchers working in the multidisciplinary areas use this book to discover the current developments. Besides its use in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases. Medical institutions use this book as reference material and give tutorials to medical experts on how the advanced AI and ML techniques contribute to the diagnosis and prediction of the diseases.

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