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Elsevier

Mining Biomedical Text, Images and Visual Features for Information Retrieval

  • 1st Edition - November 15, 2024
  • Latest edition
  • Editors: Sujata Dash, Subhendu Kumar Pani, Wellington Pinheiro Dos Santos, Jake Y Chen
  • Language: English

Mining Biomedical Text, Images and Visual Features for Information Retrieval provides broad coverage of the concepts, themes, and instrumentalities of the important, evolvi… Read more

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Description

Mining Biomedical Text, Images and Visual Features for Information Retrieval provides broad coverage of the concepts, themes, and instrumentalities of the important, evolving area of biomedical text, images, and visual features towards information retrieval. The book aims to encourage an even wider adoption of IR methods for assisting in problem-solving and to stimulate research that may lead to additional innovations in this area of research. Topics covered include Internet of Things for health informatics; data privacy; smart healthcare; medical image processing; 3D medical images; evolutionary computing; deep learning; medical ontology; linguistic indexing; lexical analysis; and domain specific semantic categories in biomedical applications. This is a valuable resource for researchers and graduate students who are interested to learn more about data mining techniques to improve their research work.

Key features

  • Describes many biomedical imaging techniques to detect diseases at the cellular level i.e., image segmentation, classification, or image indexing using a variety of computational intelligence and image processing approaches
  • Discusses how data mining techniques can be used for noise diminution and filtering MRI, EEG, MEG, fMRI, fNIRS, and PET Images
  • Presents text mining techniques used for clinical documents in the areas of medicine and Biomedical NLP Systems

Readership

Researchers and graduate students in medical informatics/bioinformatics, Researchers and graduate students in life sciences programs

Table of contents

Part I: IoT for Biomedical and Health Informatics

1. Introduction to IoT and Health Informatics

2. IoT system architectures in healthcare

3. Computational Intelligence in IoT Healthcare

4. Data Privacy in IoT E-health

5. IoT big data analytics in the healthcare industry.

6. Methodical IoT Based Information System in Healthcare Industry.

7. IoT for Smart Healthcare monitoring System

Part II: Computational Intelligence for Medical Image Processing

8. Computational Intelligence approaches in Biomedical image Processing

9. Distributed 3-D Medical Image Registration Using Intelligent Agents

10. Image Segmentation and Parameterization for Automatic Diagnostics

11. Computational Intelligence on Medical Imaging with Artificial Neural Networks

12. Evolutionary Computing and Its Use in Medical Imaging

13. Image Informatics for Clinical and Preclinical Biomedical Analysis

14. Topic Extractions (in Psychology)

15. Deep Learning in Medical Image Analysis

16. Automatic Segmentation of Multiple Organs on CT Images by Using Deep Learning Approaches

17. Medical Image Synthesis using Deep Learning

18. Medical Image Mining Using Data Mining Techniques

19. Biomedical Image Characterization and Radio genomics Using Machine Learning Techniques

Part III: Biomedical Natural Language Processing

20. Medical Ontology for text Categorization System

21. Biomedical terminologies resources for Information Retrieval

22. Image retrieval and Linguistic Indexing

23. Translation of Biomedical terms Using inferring rewriting rules

24. Lexical Analysis of Biomedical Ontologies

25. Word Sense Disambiguation in biomedical applications

26. Domain Specific Semantic Categories in Biomedical applications

Product details

  • Edition: 1
  • Latest edition
  • Published: November 15, 2024
  • Language: English

About the editors

SD

Sujata Dash

Sujata Dash is a Professor of Information Technology at Nagaland University, India, and an IEEE Senior Member, with over three decades of academic and research experience. She holds a PhD in Computational Modeling and has also completed postdoctoral research at the University of Manitoba, Canada, where she later served as a Visiting Professor. Her research spans machine learning, deep learning, artificial intelligence, bioinformatics, natural language processing, and IoT, with applications across healthcare, data science, and smart systems. Dr. Dash has an extensive publication record with leading publishers including Elsevier, Springer, Wiley, and CRC Press, and serves on the editorial boards of several international journals. She has delivered keynote lectures and chaired sessions at numerous international conferences and has received several awards, including the Global Distinguished Award (IEEE IAS, 2023), Outstanding Scientist Award, and Best Researcher Award.

Affiliations and expertise
Professor, Department of Information Technology, School of Engineering and Technology, Nagaland University, Kohima Campus, Meriema, Nagaland, India

SK

Subhendu Kumar Pani

Subhendu Kumar Pani received his Ph.D. from Utkal University Odisha, India. He has more than 16 years of teaching and research experience. His research interests include data mining, big data analysis, web data analytics, fuzzy decision making and computational intelligence. He is a fellow in SSARSC and life member in IE, ISTE, ISCA, OBA.OMS, SMIACSIT, SMUACEE, CSI.
Affiliations and expertise
Department of Computer Science and Engineering, Krupajal Engineering College, Bhubaneswar, Odisha, India

WD

Wellington Pinheiro Dos Santos

Professor dos Santos is creator and developer of innovative healthcare solutions for diagnosis and treatment using Artificial Intelligence. Applications in digital epidemiology, neuroscience, diagnostic imaging, diagnosis by signs, diagnosis by laboratory tests, health informatics and bioinformatics. Founder of the Ada Lovelace Association. Leader of the Research Group on Biomedical Computing at UFPE. Enthusiast of social entrepreneurship and innovation in health.
Affiliations and expertise
Professor of Biomedical Engineering, Federal University of Pernambuco, Brazil

JY

Jake Y Chen

Before joining UAB, Dr. Chen was the founding director of the Indiana Center for Systems Biology and Personalized Medicine at Indiana University and a tenured faculty member at Indiana University School of Informatics and Purdue University Computer Science Department. Dr. Chen has over 20 years of research and development experience in biological data mining, systems biology, and translational informatics in both Academia and the industry. He has over 150 peer-reviewed publications and presented worldwide on topics related to biocomputing, bioinformatics, and data sciences in life sciences. He was elected as the President-elect of the Midsouth Computational Biology and Bioinformatics Society (MCBIOS) in 2019. He also serves on the editorial boards of BMC Bioinformatics, Journal of American Medical Informatics Association (JAMIA), and Personalized Medicine.
Affiliations and expertise
Associate Director and Chief Bioinformatics Officer of the University of Alabama-Birmingham (UAB) Informatics Institute Professor of Genetics, Computer Science, and Biomedical Engineering, and Chief of the Informatics Section of the UAB School of Medicine, Department of Genetics, Birmingham, AL, USA

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