Machine Learning Healthcare by Panesar Arjun (32 results)

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Paperback or Softback. Condition: New. Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes. Book.

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Paperback. Condition: New. 2nd ed. This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand 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.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth 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.

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Paperback. Condition: New. 2nd ed. This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand 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.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth 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.

Paperback. Condition: new. Paperback. This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand how machine learning can be used to develop health intelligencewith the aim of improving patient health, population health, and facilitating significant care-payer cost savings.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth 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. Intermediate user level Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New. 2020. 2nd ed. Paperback. . . . . .

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Condition: New. 2020. 2nd ed. Paperback. . . . . . Books ship from the US and Ireland.

Paperback. Condition: Brand New. 2nd edition. 407 pages. 9.75x7.00x1.00 inches. In Stock.

Paperback. Condition: New. 2nd ed. This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand 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.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth 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.

Condition: New. 2nd ed. edition NO-PA16APR2015-KAP.

Paperback. Condition: new. Paperback. This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand how machine learning can be used to develop health intelligencewith the aim of improving patient health, population health, and facilitating significant care-payer cost savings.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth 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. Intermediate user level Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condition: Neu. Machine Learning and AI for Healthcare | Big Data for Improved Health Outcomes | Arjun Panesar | Taschenbuch | xxx | Englisch | 2020 | Apress | EAN 9781484265369 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Paperback. Condition: New. 2nd ed. This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand 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.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth 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.

Condition: new. Questo è un articolo print on demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand 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.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth care professionalsinterested 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. 440 pp. Englisch.

Condition: New. Print on Demand.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Intermediate user level|Offers healthcare professionals a tech jargon-free understanding of the applications of machine learning in healthcareCovers the ethics of data and learning governance and the hurdles that require .

Condition: New. PRINT ON DEMAND.