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Artificial Intelligence for Data-Driven Medical Diagnosis

2021-02-08 Computers
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Release : 2021-02-08
Genre : Computers
Kind : eBook
Book Rating : 386/5 ( reviews)

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Book Synopsis Artificial Intelligence for Data-Driven Medical Diagnosis by : Deepak Gupta

Download or read book Artificial Intelligence for Data-Driven Medical Diagnosis written by Deepak Gupta. This book was released on 2021-02-08. Available in PDF, EPUB and Kindle. Book excerpt: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

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 for Data-Driven Medical Diagnosis

2021-02-08 Computers
Download Artificial Intelligence for Data-Driven Medical Diagnosis PDF Online Free

Author :
Release : 2021-02-08
Genre : Computers
Kind : eBook
Book Rating : 327/5 ( reviews)

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Book Synopsis Artificial Intelligence for Data-Driven Medical Diagnosis by : Deepak Gupta

Download or read book Artificial Intelligence for Data-Driven Medical Diagnosis written by Deepak Gupta. This book was released on 2021-02-08. Available in PDF, EPUB and Kindle. Book excerpt: This book collects research works of data-driven medical diagnosis done via Artificial Intelligence based solutions, such as Machine Learning, Deep Learning and Intelligent Optimization. Physical devices powered with Artificial Intelligence are gaining importance in diagnosis and healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.

Data Driven Approaches for Healthcare

2019-10-01 Business & Economics
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Release : 2019-10-01
Genre : Business & Economics
Kind : eBook
Book Rating : 038/5 ( reviews)

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Book Synopsis Data Driven Approaches for Healthcare by : Chengliang Yang

Download or read book Data Driven Approaches for Healthcare written by Chengliang Yang. This book was released on 2019-10-01. Available in PDF, EPUB and Kindle. Book excerpt: Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients’ acute and chronic condition loads and demographic characteristics

Future of AI in Medical Imaging

2024-03-11 Computers
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Release : 2024-03-11
Genre : Computers
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Future of AI in Medical Imaging by : Sharma, Avinash Kumar

Download or read book Future of AI in Medical Imaging written by Sharma, Avinash Kumar. This book was released on 2024-03-11. Available in PDF, EPUB and Kindle. Book excerpt: Academic scholars and professionals are currently grappling with hurdles in optimizing diagnostic processes, as traditional methodologies prove insufficient in managing the intricate and voluminous nature of medical data. The diverse range of imaging techniques, spanning from endoscopy to magnetic resonance imaging, necessitates a more unified and efficient approach. This complexity has created a pressing need for streamlined methodologies and innovative solutions. Academic scholars find themselves at the forefront of addressing these challenges, seeking ways to leverage AI's full potential in improving the accuracy of medical imaging diagnostics and, consequently, enhancing overall patient outcomes. Future of AI in Medical Imaging, stands as a solution to the challenges faced by academic scholars in the realm of medical imaging. The book lays a solid groundwork for understanding the complexities of medical imaging systems. Through an exploration of various imaging modalities, it not only addresses the current issues but also serves as a guide for scholars to navigate the landscape of AI-integrated medical diagnostics. This collaborative effort not only illuminates the existing hurdles of medical imaging but also looks towards a future where AI-driven diagnostics and personalized medicine become indispensable tools, significantly elevating patient outcomes.

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