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Deep Learning in Medical Signal and Image Processing

  • Muhammad Aamir
  • , Uzair Aslam Bhatti
  • , Ziaur Rahman
  • , Jameel Ahmed Bhutto
  • , Waheed Ahmed Abro

Research output: Book/ReportBookpeer-review

Abstract

Deep learning is revolutionizing the analysis of medical signals and images, offering unprecedented advancements in diagnostic accuracy and efficiency. Techniques such as convolutional and recurrent neural networks are transforming the processing of radiological scans, ultrasound images, and ECG readings. By enabling more detailed and precise interpretations, deep learning enhances the ability of healthcare providers to make timely and informed decisions. These innovations are reshaping medical workflows, improving patient outcomes, and paving the way for a future of more reliable and efficient healthcare solutions.Deep Learning in Medical Signal and Image Processing offers a comprehensive examination of deep learning, specifically through convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to medical data. It explores the application of AI in the analysis of medical signals and images. Covering topics such as diagnostic accuracy, enhanced decision-making, and data augmentation techniques, this book is an excellent resource for medical practitioners, clinicians, data scientists, AI researchers, healthcare professionals, engineers, professionals, researchers, scholars, academicians, and more.

Original languageEnglish
PublisherIGI Global
Number of pages608
ISBN (Electronic)9798369398180
ISBN (Print)9798369398166
DOIs
StatePublished - 1 Jan 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025 by IGI Global Scientific Publishing. All rights reserved.

ASJC Scopus subject areas

  • General Computer Science
  • General Medicine
  • General Engineering

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