Applications of Parallel Data Processing for Biomedical Imaging

Applications of Parallel Data Processing for Biomedical Imaging
Author :
Publisher : IGI Global
Total Pages : 367
Release :
ISBN-10 : 9798369324271
ISBN-13 :
Rating : 4/5 (71 Downloads)

Book Synopsis Applications of Parallel Data Processing for Biomedical Imaging by : Khan, Rijwan

Download or read book Applications of Parallel Data Processing for Biomedical Imaging written by Khan, Rijwan and published by IGI Global. This book was released on 2024-04-26 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the remarkable progress witnessed in the last decade in big data utilization and parallel processing techniques, a persistent disparity exists between the capabilities of computer-aided diagnosis systems and the intricacies of practical healthcare scenarios. This disconnection is particularly evident in the complex landscape of artificial intelligence (AI) and IoT innovations within the biomedical realm. The need to bridge this gap and explore the untapped potential in healthcare and biomedical applications has never been more crucial. As we navigate through these challenges, Applications of Parallel Data Processing for Biomedical Imaging offers insights and solutions to reshape the future of biomedical research. The objective of Applications of Parallel Data Processing for Biomedical Imaging is to bring together researchers from both the computer science and biomedical research communities. By showcasing state-of-the-art deep learning and large data analysis technologies, the book provides a platform for the cross-pollination of ideas between AI-based and traditional methodologies. The collaborative effort seeks to have a substantial impact on data mining, AI, computer vision, biomedical research, healthcare engineering, and other related fields. This interdisciplinary approach positions the book as a cornerstone for scholars, professors, and professionals working in software and medical fields, catering to both graduate and undergraduate students eager to explore the evolving landscape of parallel computing, artificial intelligence, and their applications in biomedical research.


Applications of Parallel Data Processing for Biomedical Imaging Related Books

Applications of Parallel Data Processing for Biomedical Imaging
Language: en
Pages: 367
Authors: Khan, Rijwan
Categories: Medical
Type: BOOK - Published: 2024-04-26 - Publisher: IGI Global

DOWNLOAD EBOOK

Despite the remarkable progress witnessed in the last decade in big data utilization and parallel processing techniques, a persistent disparity exists between t
Reshaping Healthcare with Cutting-Edge Biomedical Advancements
Language: en
Pages: 504
Authors: Prabhakar, Pranav Kumar
Categories: Technology & Engineering
Type: BOOK - Published: 2024-05-06 - Publisher: IGI Global

DOWNLOAD EBOOK

Despite remarkable advancements in biomedical research, the healthcare industry faces challenges in effectively translating these discoveries into tangible pati
Exploring Medical Statistics: Biostatistics, Clinical Trials, and Epidemiology
Language: en
Pages: 356
Authors: Arora, Geeta
Categories: Medical
Type: BOOK - Published: 2024-07-18 - Publisher: IGI Global

DOWNLOAD EBOOK

In today's data-driven world, understanding and interpreting statistical information is more critical than ever, especially in medicine, where statistical metho
Ethnobotanical Insights Into Medicinal Plants
Language: en
Pages: 406
Authors: Musaddiq, Sara
Categories: Medical
Type: BOOK - Published: 2024-05-07 - Publisher: IGI Global

DOWNLOAD EBOOK

A significant gap exists between traditional knowledge and modern scientific understanding of phytochemicals and ethnobotanical wisdom in botanical science. Des
Convergence of Population Health Management, Pharmacogenomics, and Patient-Centered Care
Language: en
Pages: 578
Authors: Moumtzoglou, Anastasius S.
Categories: Medical
Type: BOOK - Published: 2024-09-27 - Publisher: IGI Global

DOWNLOAD EBOOK

The current healthcare framework, often characterized by standardized treatments and one-size-fits-all approaches, falls short in addressing the unique genetic