Product details:
ISBN13: | 9780443154522 |
ISBN10: | 044315452X |
Binding: | Paperback |
No. of pages: | 668 pages |
Size: | 235x191 mm |
Weight: | 450 g |
Language: | English |
697 |
Category:
Mining Biomedical Text, Images and Visual Features for Information Retrieval
Publisher: Academic Press
Date of Publication: 20 November 2024
Normal price:
Publisher's listprice:
EUR 143.00
EUR 143.00
Your price:
49 730 (47 362 HUF + 5% VAT )
discount is: 20% (approx 12 432 HUF off)
Discount is valid until: 31 December 2024
The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
Click here to subscribe.
Click here to subscribe.
Availability:
printed on demand
Can't you provide more accurate information?
Long 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.
- 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
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
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