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결과 내 검색 동의어 포함

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목차보기


1. What Is Artificial Intelligence?
2. Data
3. What Is Machine Learning?
4. Machine Learning Algorithms
5. Evaluating Learning for Intelligence
6. Ethics of Intelligence
7. Future of Healthcare
8. Case Studies
Technical glossary
References
Index

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Machine learning and AI for healthcare : big data for improved health outcomes 이용현황 표 - 등록번호, 청구기호, 권별정보, 자료실, 이용여부로 구성 되어있습니다.
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알라딘제공

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges.

You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization.   You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. 

Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things.


What You'll Learn
  • Gain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare 
  • Implement machine learning systems, such as speech recognition and enhanced deep learning/AI
  • Select learning methods/algorithms and tuning for use in healthcare
  • Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agents
Who This Book Is For

Health care professionals interested in how machine learning can be used to develop health intelligence ? with the aim of improving patient health, population health and facilitating significant care-payer cost savings.


New feature

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges.

You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. 

Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things.





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