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Big Data and Artificial Intelligence for Healthcare Applications / Ankur Saxena.

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Florida : CRC Press, 2021.Edition: 1st edDescription: xii, 274 p. : ill. ; 24 cmISBN:
  • 9780367554958
  • 9781003093770
Uniform titles:
  • Big Data and Artificial Intelligence for Healthcare Applications
Subject(s): DDC classification:
  • 23 610.285 SAX
Contents:
Part I: Conceptual. 1. Introduction to Big Data. 2. Introduction to Machine Learning. Part II: Application. 3. Machine Learning in Clinical Trials. 4. Deep Learning and Its Biological and Biomedical Applications. 5. Applications of Machine Learning Algorithms to Cancer Data. 6. Pancreatic Cancer Detection by an Integrated Level Set-Based Deep Learning Model. 7. Early and Precision-Oriented Detection of Cervical Cancer. 8. Transformation of mHealth in Society. 9. Artificial Intelligence and Deep Learning for Medical Diagnosis and Treatment. Part III: Ethics. 10. Ethical Issues and Challenges with Artificial Intelligence in Healthcare. 11. Epistemological Issues and Challenges with Artificial Intelligence in Healthcare.
Summary: This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.
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Text Books Text Books CUTN Central Library Medicine, Technology & Management Non-fiction 610.285 SAX (Browse shelf(Opens below)) Available 47789

Part I: Conceptual. 1. Introduction to Big Data. 2. Introduction to Machine Learning. Part II: Application. 3. Machine Learning in Clinical Trials. 4. Deep Learning and Its Biological and Biomedical Applications. 5. Applications of Machine Learning Algorithms to Cancer Data. 6. Pancreatic Cancer Detection by an Integrated Level Set-Based Deep Learning Model. 7. Early and Precision-Oriented Detection of Cervical Cancer. 8. Transformation of mHealth in Society. 9. Artificial Intelligence and Deep Learning for Medical Diagnosis and Treatment. Part III: Ethics. 10. Ethical Issues and Challenges with Artificial Intelligence in Healthcare. 11. Epistemological Issues and Challenges with Artificial Intelligence in Healthcare.

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research.

"Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare.

Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

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