Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes

Arjun Panesar

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Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes-preview-1

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商品描述

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.

商品描述(中文翻譯)

探索人工智慧(AI)和機器學習在醫療保健領域的理論和實際應用。本書提供了機器學習算法、架構設計以及在醫療保健和大數據挑戰中的應用的指導之旅。

您將了解醫療保健數據分析的道德影響以及人口和患者健康優化中人工智慧的未來。您還將在組織內創建機器學習模型,評估其性能並將其成果應用於運營中。

《機器學習和人工智慧在醫療保健中的應用》提供了如何在組織內應用機器學習以及評估人工智慧應用的效力、適用性和效率的技巧。這些技巧通過領先的案例研究加以說明,包括患者主導數據學習和物聯網如何重新定義慢性疾病。

您將學到什麼

- 深入了解關鍵機器學習算法及其在更廣泛的醫療保健領域中的使用和實施
- 實施語音識別和增強型深度學習/人工智慧等機器學習系統
- 選擇適用於醫療保健的學習方法/算法和調整
- 通過最佳實踐、反饋循環和智能代理認識和為醫療保健中的人工智慧未來做好準備

本書適合對象

對如何利用機器學習開發健康智能(以改善患者健康、人口健康並實現重大醫療保險支付成本節約)感興趣的醫療保健專業人士。