Diagnosis of Neurological Disorders Based on Deep Learning Techniques
暫譯: 基於深度學習技術的神經系統疾病診斷

Chaki, Jyotismita

Diagnosis of Neurological Disorders Based on Deep Learning Techniques
  • 出版商: CRC
  • 出版日期: 2025-01-30
  • 售價: $2,810
  • 貴賓價: 9.5 折 $2,670
  • 語言: 英文
  • 頁數: 222
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032325240
  • ISBN-13: 9781032325248
  • 相關分類: DeepLearning

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商品描述

This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks in the field of diagnosis of neurological disorders. Along with this, data preprocessing including scaling, correction, trimming, and normalization is also included.

  • Offers a detailed description of the deep learning approaches used for the diagnosis of neurological disorders.

  • Demonstrates concepts of deep learning algorithms using diagrams, data tables, and examples for the diagnosis of neurodegenerative, neurodevelopmental, and psychiatric disorders.

  • Helps build, train, and deploy different types of deep architectures for diagnosis.

  • Explores data preprocessing techniques involved in diagnosis.

  • Includes real-time case studies and examples.

This book is aimed at graduate students and researchers in biomedical imaging and machine learning.

商品描述(中文翻譯)

本書基於深度學習方法，用於神經系統疾病的診斷，包括使用圖表、數據表和實際範例來介紹深度學習演算法的基本概念，以診斷神經退行性和神經發展性疾病。內容涵蓋了前饋神經網絡（feed-forward neural networks）、深度生成模型（deep generative models）、卷積神經網絡（convolutional neural networks）、圖卷積網絡（graph convolutional networks）和遞迴神經網絡（recurrent neural networks）在神經系統疾病診斷領域的應用。此外，還包括數據預處理技術，包括縮放、校正、修剪和正規化。

- 提供用於神經系統疾病診斷的深度學習方法的詳細描述。
- 使用圖表、數據表和範例展示深度學習演算法的概念，以診斷神經退行性、神經發展性和精神疾病。
- 幫助構建、訓練和部署不同類型的深度架構以進行診斷。
- 探索與診斷相關的數據預處理技術。
- 包含實時案例研究和範例。

本書旨在為生物醫學影像和機器學習的研究生和研究人員提供參考。

作者簡介

Jyotismita Chaki, PhD, is an Associate Professor in School of Computer Science and Engineering at Vellore Institute of Technology, Vellore, India. She gained her PhD (Engg.) from Jadavpur University, Kolkata, India. Her research interests include computer vision and image processing, pattern recognition, medical imaging, artificial intelligence, and machine learning. Jyotismita has authored more than 40 international conference and journal papers and is the author and editor of more than eight books. Currently, she is the Academic Editor of PLOS One journal and PeerJ Computer Science journal and Associate Editor of IET Image Processing journal, Array journal, and Machine Learning with Applications journal.

作者簡介(中文翻譯)

Jyotismita Chaki 博士是印度維洛爾科技學院計算機科學與工程學院的副教授。她在印度加爾各答的賈達夫普大學獲得工程學博士學位。她的研究興趣包括計算機視覺與影像處理、模式識別、醫學影像、人工智慧和機器學習。Jyotismita 已發表超過 40 篇國際會議和期刊論文，並且是超過八本書籍的作者和編輯。目前，她是 PLOS One 期刊和 PeerJ Computer Science 期刊的學術編輯，以及 IET Image Processing 期刊、Array 期刊和 Machine Learning with Applications 期刊的副編輯。

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