Produktbild: Mining Biomedical Text, Images and Visual Features for Information Retrieval

Mining Biomedical Text, Images and Visual Features for Information Retrieval

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

20.11.2024

Herausgeber

Sujata Dash + weitere

Verlag

Elsevier Science & Technology

Seitenzahl

668

Maße (L/B/H)

23.5/19.1/3.1 cm

Gewicht

1380 g

Sprache

Englisch

ISBN

978-0-443-15452-2

Beschreibung

Portrait

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.

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.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

20.11.2024

Herausgeber

Verlag

Elsevier Science & Technology

Seitenzahl

668

Maße (L/B/H)

23.5/19.1/3.1 cm

Gewicht

1380 g

Sprache

Englisch

ISBN

978-0-443-15452-2

EU-Ansprechpartner

Zeitfracht Medien GmbH
Ferdinand-Jühlke-Straße 7
99095 Erfurt
DE
produktsicherheit@zeitfracht.de

Herstelleradresse

Elsevier Science & Technology
London Wall 125
EC2Y 5AS London
GB
tradeorders@elsevier.com

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  • Produktbild: Mining Biomedical Text, Images and Visual Features for Information Retrieval
  • 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