Mining Biomedical Text, Images and Visual Features for Information Retrieval
Published on 15. November 2024
500 pages
978-0-443-15451-5 (ISBN)
Description
Mining Biomedical Text, Images and Visual Features for Information Retrieval provides the reader with a broad coverage of the concepts, themes, and instrumentalities of the important and evolving area of biomedical text, images, and visual features towards information retrieval. It 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.The book discusses topics such as 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.It is a valuable resource for researchers and graduate students who are interested to learn more about data mining techniques to improve their research work.
- 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
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Sujata Dash | Subhendu Kumar Pani | Wellington Pinheiro Dos Santos
Mining Biomedical Text, Images and Visual Features for Information Retrieval
Book
11/2024
Academic Press
€152.50
Shipment within 15-20 days
Content
Part I: IoT for Biomedical and Health Informatics1. Introduction to IoT and Health Informatics2. IoT system architectures in healthcare3. Computational Intelligence in IoT Healthcare4. Data Privacy in IoT E-health5. IoT big data analytics in the healthcare industry.6. Methodical IoT Based Information System in Healthcare Industry.7. IoT for Smart Healthcare monitoring SystemPart II: Computational Intelligence for Medical Image Processing8. Computational Intelligence approaches in Biomedical image Processing9. Distributed 3-D Medical Image Registration Using Intelligent Agents10. Image Segmentation and Parameterization for Automatic Diagnostics11. Computational Intelligence on Medical Imaging with Artificial Neural Networks12. Evolutionary Computing and Its Use in Medical Imaging13. Image Informatics for Clinical and Preclinical Biomedical Analysis14. Topic Extractions (in Psychology)15. Deep Learning in Medical Image Analysis16. Automatic Segmentation of Multiple Organs on CT Images by Using Deep Learning Approaches17. Medical Image Synthesis using Deep Learning18. Medical Image Mining Using Data Mining Techniques19. Biomedical Image Characterization and Radio genomics Using Machine Learning TechniquesPart III: Biomedical Natural Language Processing20. Medical Ontology for text Categorization System21. Biomedical terminologies resources for Information Retrieval22. Image retrieval and Linguistic Indexing23. Translation of Biomedical terms Using inferring rewriting rules24. Lexical Analysis of Biomedical Ontologies25. Word Sense Disambiguation in biomedical applications26. Domain Specific Semantic Categories in Biomedical applications
