Mining Biomedical Text, Images and Visual Features for Information Retrieval

Sujata Dash holds the position of Professor at the Information Technology School of Engineering and Technology, Nagaland University, Dimapur Campus, Nagaland, India, bringing more than three decades of dedicated service in teaching and mentoring students. She has been honoured with the prestigious Titular Fellowship from the Association of Commonwealth Universities, United Kingdom. As a testament to her global contributions, she served as a visiting professor in the Computer Science Department at the University of Manitoba, Canada. With a prolific academic record, she has authored over 200 technical papers published in esteemed international journals, and conference proceedings, and edited book chapters by reputed publishers such as Springer, Elsevier, IEEE, IGI Global USA, and Wiley. Dr. Dash boasts ten patents, two copyrights, numerous textbooks, and edited books to her credit. Actively engaged in professional associations, she is a life member of renowned international bodies like ACM, IRSS, CSI, IMS, OITS, OMS, IACSIT, and IST, and holds a Senior membership in IEEE. Serving as a reviewer and Associate Editor for approximately 15 international journals, including prestigious publications like World Scientific, Bioinformatics, Springer, IEEE ACCESS, Inderscience, and Science Direct, she significantly contributes to the scholarly review process. Dr. Dash has been honoured with various national and international awards and serves on the editorial boards of around ten international journals. Her global presence extends to delivering keynote speeches, invited talks, and chairing special sessions at international conferences in India and overseas. Her research expertise encompasses Biomedical and Healthcare, Machine Learning, Deep Learning, Data Science, Big Data Analytics, Bioinformatics, and Intelligent Agents. 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. 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. 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.

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