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Healthcare Solutions Using Machine Learning and Informatics [Paperback]

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  • Category: Books (Medical)
  • ISBN-10:  1032345225
  • ISBN-10:  1032345225
  • ISBN-13:  9781032345222
  • ISBN-13:  9781032345222
  • Publisher:  Auerbach Publications
  • Publisher:  Auerbach Publications
  • Pages:  266
  • Pages:  266
  • Binding:  Paperback
  • Binding:  Paperback
  • SKU:  1032345225-11-MPOD
  • SKU:  1032345225-11-MPOD
  • Item ID: 107087344
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Oct 14 to Oct 16
  • Notes: Brand New Item. Not shipped to AK, HI, APO, FPO, AE.
Focuses on fundamental concepts of gathering, processing, analyzing the dataset from rich healthcare and biomedical sources. Covers interdisciplinary techniques such as data science, deep learning, statistics, big data analytics, smart devices, computer vision and IoT.

1. Introduction to Artificial Intelligence in Healthcare 2. Machine Learning in Radio Imagining 3. Solutions Using Machine Learning for Diabetes 4. A Highly Reliable Machine Learning Algorithm for Cardiovascular Disease Prediction 5. Machine Learning Algorithm for Industry Using Image Sensing 6. Solutions Using Machine Learning For COVID-19 7. Big Data Analytics in Healthcare Data Processing 8. Reliable Biomedical Applications Using AI Models 9. Disease Detection Using Imaging Sensors, Deep Learning and Machine Learning for Smart Farming 10. IoT Application for Healthcare 11. Machine Learning Algorithm for Diabetes Disease Prediction 12. Use of Machine Learning in Healthcare

Healthcare Solutions Using Machine Learning and Informatics covers novel and innovative solutions for healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, and intelligent IoT-based solutions for medical image analysis, medical big-data processing, and disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence.

The wide variety of topics covered include:

  • Artificial Intelligence in healthcare
  • Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19
  • Big data analytics solutions for healthcare data processing
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