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Titlebook: Leveraging Data Science for Global Health; Leo Anthony Celi,Maimuna S. Majumder,Melek Somai Textbook‘‘‘‘‘‘‘‘ 2020 The Editor(s) (if applic

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楼主: Enkephalin
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Textbook‘‘‘‘‘‘‘‘ 2020strophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient..
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Biomedical Signal Processing: An ECG Applicationelet transform on multi-channel ECG signals from patients with arrhythmias. The information extracted is used to develop a high-performing heartbeat classifier that can distinguish between various types of regular and irregular beats.
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An Introduction to Design Thinking and an Application to the Challenges of Frail, Older Adultsegies and solutions. This process generally leads to a more holistic and sustainable intervention, improving outcomes and adoption. This chapter provides a primer to design thinking, as well an introductory toolkit to begin applying the approach to your innovations.
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Applied Statistical Learning in Pythonns in medicine. Thus, it is by no means a comprehensive guide on machine learning or Python. Rather, my hope is to present basic concepts in a simple, creative way, and demonstrate how they can be applied together.
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sources.Focuses on combating disease and promoting health, .This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the applicati
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Textbook‘‘‘‘‘‘‘‘ 2020rce-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healt
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