Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
暫譯: 醫療保健的機器學習與人工智慧:利用大數據改善健康結果
Arjun Panesar
- 出版商: Apress
- 出版日期: 2019-02-05
- 售價: $1,550
- 貴賓價: 9.5 折 $1,473
- 語言: 英文
- 頁數: 368
- 裝訂: Paperback
- ISBN: 1484237986
- ISBN-13: 9781484237984
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相關分類:
人工智慧、大數據 Big-data、Machine Learning
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其他版本:
Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
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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.
- 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
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中的理論和實際應用。本書提供了機器學習演算法、架構設計以及在醫療保健和大數據挑戰中學習應用的導覽。
您將發現醫療數據分析的倫理影響以及AI在優化人口和病人健康方面的未來。您還將創建一個機器學習模型,評估其性能並在您的組織內實現其結果。
《機器學習與醫療保健中的AI》提供了如何在您的組織內應用機器學習的技術,並評估AI應用的有效性、適用性和效率。這些技術通過領先的案例研究進行說明,包括如何通過病人主導的數據學習和物聯網重新定義慢性疾病。
您將學到的內容:
- 深入了解關鍵的機器學習演算法及其在更廣泛醫療保健中的使用和實施
- 實施機器學習系統,例如語音識別和增強的深度學習/AI
- 選擇適用於醫療保健的學習方法/演算法並進行調整
- 通過最佳實踐、反饋循環和智能代理,認識並為醫療保健中人工智慧的未來做好準備
本書適合對機器學習如何用於發展健康智能感興趣的醫療保健專業人員,旨在改善病人健康、人口健康並促進顯著的護理支付者成本節省。