Big Data Analysis and Artificial Intelligence for Medical Sciences
eBook - PDF

Big Data Analysis and Artificial Intelligence for Medical Sciences

  1. English
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  3. Available on iOS & Android
eBook - PDF

Big Data Analysis and Artificial Intelligence for Medical Sciences

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About This Book

Big Data Analysis and Artificial Intelligence for Medical Sciences

Overview of the current state of the art on the use of artificial intelligence in medicine and biology

Big Data Analysis and Artificial Intelligence for Medical Sciences demonstrates the efforts made in the fields of Computational Biology and medical sciences to design and implement robust, accurate, and efficient computer algorithms for modeling the behavior of complex biological systems much faster than using traditional modeling approaches based solely on theory.

With chapters written by international experts in the field of medical and biological research, Big Data Analysis and Artificial Intelligence for Medical Sciences includes information on:

  • Studies conducted by the authors which are the result of years of interdisciplinary collaborations with clinicians, computer scientists, mathematicians, and engineers
  • Differences between traditional computational approaches to data processing (those of mathematical biology) versus the experiment-data-theory-model-validation cycle
  • Existing approaches to the use of big data in the healthcare industry, such as through IBM's Watson Oncology, Microsoft's Hanover, and Google's DeepMind
  • Difficulties in the field that have arisen as a result of technological changes, and potential future directions these changes may take

A timely and up-to-date resource on the integration of artificial intelligence in medicine and biology, Big Data Analysis and Artificial Intelligence for Medical Sciences is of great benefit not only to professional scholars, but also MSc or PhD program students eager to explore advancement in the field.

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Yes, you can access Big Data Analysis and Artificial Intelligence for Medical Sciences by Bruno Carpentieri,Paola Lecca in PDF and/or ePUB format, as well as other popular books in Medicine & Biostatistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2024
ISBN
9781119846543
Edition
1
Topic
Medicine
Subtopic
Biostatistics

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Contents
  5. List of Contributors
  6. Preface
  7. Chapter 1 Introduction
  8. Chapter 2 Fuzzy Logic for Knowledge‐Driven and Data‐Driven Modeling in Biomedical Sciences
  9. Chapter 3 Application of Machine Learning Algorithms to Diagnosis and Prognosis of Chronic Wounds
  10. Chapter 4 Deep Learning Techniques for Gene Identification in Cancer Prevention
  11. Chapter 5 Deep Learning for Network Biology
  12. Chapter 6 Deep Learning‐Based Reduced Order Models for Cardiac Electrophysiology
  13. Chapter 7 The Potential of Microbiome Big Data in Precision Medicine: Predicting Outcomes Through Machine Learning
  14. Chapter 8 Predictive Patient Stratification Using Artificial Intelligence and Machine Learning
  15. Chapter 9 Hybrid Data‐Driven and Numerical Modeling of Articular Cartilage
  16. Chapter 10 A Hybrid of Differential Evolution and Minimization of Metabolic Adjustment for Succinic and Ethanol Production
  17. Chapter 11 Analysis Pipelines and a Platform Solution for Next‐Generation Sequencing Data
  18. Chapter 12 Artificial Intelligence: From Drug Discovery to Clinical Pharmacology
  19. Chapter 13 Using AI to Steer Brain Regeneration: The Enhanced Regenerative Medicine Paradigm
  20. Chapter 14 Towards Better Ways to Assess Predictive Computing in Medicine: On Reliability, Robustness, and Utility
  21. Chapter 15 Legal Aspects of AI in the Biomedical Field. The Role of Interpretable Models
  22. Chapter 16 The Long Path to Usable AI
  23. Index
  24. EULA