IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences write by Dino Quintero. This book was released on 2019-09-08. IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences available in PDF, EPUB and Kindle. This IBM® Redpaper publication provides an update to the original description of IBM Reference Architecture for Genomics. This paper expands the reference architecture to cover all of the major vertical areas of healthcare and life sciences industries, such as genomics, imaging, and clinical and translational research. The architecture was renamed IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences to reflect the fact that it incorporates key building blocks for high-performance computing (HPC) and software-defined storage, and that it supports an expanding infrastructure of leading industry partners, platforms, and frameworks. The reference architecture defines a highly flexible, scalable, and cost-effective platform for accessing, managing, storing, sharing, integrating, and analyzing big data, which can be deployed on-premises, in the cloud, or as a hybrid of the two. IT organizations can use the reference architecture as a high-level guide for overcoming data management challenges and processing bottlenecks that are frequently encountered in personalized healthcare initiatives, and in compute-intensive and data-intensive biomedical workloads. This reference architecture also provides a framework and context for modern healthcare and life sciences institutions to adopt cutting-edge technologies, such as cognitive life sciences solutions, machine learning and deep learning, Spark for analytics, and cloud computing. To illustrate these points, this paper includes case studies describing how clients and IBM Business Partners alike used the reference architecture in the deployments of demanding infrastructures for precision medicine. This publication targets technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing life sciences solutions and support.
IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences
IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences write by Dino Quintero. This book was released on 2019. IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences available in PDF, EPUB and Kindle.
The Digital Pill
The Digital Pill - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Digital Pill write by Elgar Fleisch. This book was released on 2021-03-22. The Digital Pill available in PDF, EPUB and Kindle. The Digital Pill reflects on apps and digital projects launched by pharmaceutical companies in recent years, as well as the first accreditations for digital pills already issued by recognised regulators. The Digital Pill is essential reading for anyone working in, engaged with or interested in understanding the e-health community.
Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover
Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover write by Joseph Dain. This book was released on 2020-08-11. Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover available in PDF, EPUB and Kindle. This IBM® Redpaper publication explains how IBM Spectrum® Discover integrates with the IBM Watson® Knowledge Catalog (WKC) component of IBM Cloud® Pak for Data (IBM CP4D) to make the enriched catalog content in IBM Spectrum Discover along with the associated data available in WKC and IBM CP4D. From an end-to-end IBM solution point of view, IBM CP4D and WKC provide state-of-the-art data governance, collaboration, and artificial intelligence (AI) and analytics tools, and IBM Spectrum Discover complements these features by adding support for unstructured data on large-scale file and object storage systems on premises and in the cloud. Many organizations face challenges to manage unstructured data. Some challenges that companies face include: Pinpointing and activating relevant data for large-scale analytics, machine learning (ML) and deep learning (DL) workloads. Lacking the fine-grained visibility that is needed to map data to business priorities. Removing redundant, obsolete, and trivial (ROT) data and identifying data that can be moved to a lower-cost storage tier. Identifying and classifying sensitive data as it relates to various compliance mandates, such as the General Data Privacy Regulation (GDPR), Payment Card Industry Data Security Standards (PCI-DSS), and the Health Information Portability and Accountability Act (HIPAA). This paper describes how IBM Spectrum Discover provides seamless integration of data in IBM Storage with IBM Watson Knowledge Catalog (WKC). Features include: Event-based cataloging and tagging of unstructured data across the enterprise. Automatically inspecting and classifying over 1000 unstructured data types, including genomics and imaging specific file formats. Automatically registering assets with WKC based on IBM Spectrum Discover search and filter criteria, and by using assets in IBM CP4D. Enforcing data governance policies in WKC in IBM CP4D based on insights from IBM Spectrum Discover, and using assets in IBM CP4D. Several in-depth use cases are used that show examples of healthcare, life sciences, and financial services. IBM Spectrum Discover integration with WKC enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of data. The integration improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.
Artificial Intelligence in Healthcare
Artificial Intelligence in Healthcare - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence in Healthcare write by Adam Bohr. This book was released on 2020-06-21. Artificial Intelligence in Healthcare available in PDF, EPUB and Kindle. 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
