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Zhiqiang Zhang
Topics Covered
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Topics Covered
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Topics Covered
- What is digital medicine?
- Who are the stakeholders?
- What are the opportunities and challenges?
- Sensors and wearables in digital medicine
- The Future of Wearables
- Big data in digital medicine
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Provides a comprehensive overview of digital medicine, covering its history, current applications, and future prospects. It is written by Robert Wachter, a leading expert in the field of healthcare innovation.
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Explores the potential of artificial intelligence (AI) to transform healthcare. It covers a wide range of topics, including AI-powered diagnostics, personalized treatment plans, and the ethical implications of AI in healthcare.
Provides a clear and concise introduction to precision medicine, a rapidly growing field that uses genomic data to tailor medical treatment to individual patients.
Explores the ways in which digital medicine is empowering patients and transforming the doctor-patient relationship.
Provides a roadmap for the future of digital health. It explores the ways in which digital health technologies can be used to improve patient care, reduce costs, and improve population health.
Provides a thought-provoking look at the future of digital medicine. It explores the potential benefits and risks of digital health technologies and discusses the ethical and regulatory challenges that need to be addressed.
Provides a comprehensive overview of the latest developments in digital medicine. It covers a wide range of topics, including AI-powered diagnostics, personalized treatment plans, and the use of digital health technologies to improve population health.
Provides a practical guide to digital medicine for clinicians. It covers a wide range of topics, including the different types of digital health technologies, how to use them effectively in clinical practice, and the ethical and regulatory issues surrounding digital medicine.
Examines the convergence of wearable technology and the Internet of Things (IoT), discussing the challenges and opportunities for seamless integration and data exchange.
This comprehensive reference work examines the rapidly evolving applications of wearable technologies in healthcare and medicine, providing insights into the design, development, and deployment of wearable devices and systems to improve patient care and promote wellness.
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Provides a comprehensive overview of the wearable technology market, covering the latest trends, innovations, and use cases. It valuable resource for anyone who wants to stay up-to-date on the latest developments in wearable technology.
Provides a comprehensive overview of the principles and applications of sensors, covering a wide range of topics from basic concepts to advanced sensing technologies.
This handbook provides a comprehensive reference on sensor technologies, including their principles, applications, and design considerations.
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Focuses on the use of sensors in healthcare applications, including wearable devices, implantable sensors, and telemedicine.
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A reference for executives and policymakers who want to understand the implications of big data for the future of business and governance.
Introduces data science and its applications in business, covering topics such as data mining, data analysis, and machine learning. It provides a solid foundation for understanding the concepts and techniques involved in Big Data analysis.
Provides an in-depth introduction to machine learning, covering the fundamental concepts and algorithms used in Big Data analysis. It is written by Andrew Ng, a leading expert in machine learning, and is highly recommended for those who want to gain a deeper understanding of Big Data.
Covers the practical aspects of Big Data analytics, providing guidance on how to plan, implement, and integrate Big Data solutions in an enterprise environment. It includes discussions on NoSQL and graph databases, which are essential technologies for handling Big Data.
Provides a comprehensive guide to Hadoop, the open-source framework for Big Data processing. It covers the core concepts and components of Hadoop, as well as advanced topics such as data warehousing and machine learning.
Provides a comprehensive guide to Spark, the popular open-source framework for Big Data processing. It covers the core concepts and components of Spark, as well as advanced topics such as streaming data and machine learning.
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