Artificial Intelligence and Computational Dynamics for Biomedical Research
eBook - ePub

Artificial Intelligence and Computational Dynamics for Biomedical Research

  1. 298 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence and Computational Dynamics for Biomedical Research

About this book

This work presents the latest development in the field of computational intelligence to advance Big Data and Cloud Computing concerning applications in medical diagnosis. As forum for academia and professionals it covers state-of-the-art research challenges and issues in the digital information & knowledge management and the concerns along with the solutions adopted in these fields.

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Yes, you can access Artificial Intelligence and Computational Dynamics for Biomedical Research by Ankur Saxena, Nicolas Brault, Ankur Saxena,Nicolas Brault in PDF and/or ePUB format, as well as other popular books in Computer Science & Bioinformatics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Title Page
  2. Copyright
  3. Contents
  4. Recent advancements in biomedical research in the era of AI and ML
  5. Prediction of cardiovascular diseases using random forest and naive Bayes algorithm
  6. Big data analytics for personalized medicine
  7. Intellection of biological life in current era
  8. Integrating artificial intelligence techniques for analysis of next-generation sequencing data
  9. Artificial intelligence: the future of neuroscience
  10. Role of big data and artificial intelligence for COVID-19 and cancer diagnosis and treatments
  11. Integrating screening modalities for early and precision-oriented evidence-based screening of cervical cancer – a holistic approach
  12. Role of artificial intelligence and machine learning in diagnosis and treatment of women centric cancer
  13. The role of artificial intelligence, machine learning and deep learning in the diagnosis, prognosis and treatment of cancers primarily associated with women
  14. Oropharyngeal cancer prognosis based on clinicopathologic and quantitative imaging biomarkers with multiparametric model and machine learning methods
  15. Artificial intelligence and machine learning in healthcare: an ethical perspective
  16. Artificial intelligence in dentistry: current issues and perspectives
  17. AI for pattern recognition and objectivity: the case of melanoma detection
  18. Ethical horizons of biobank-based artificial intelligence in biomedical research
  19. Index
  20. Intelligent Biomedical Data Analysis (IBDA)