Reprint

Data Science in Healthcare

Edited by
May 2022
212 pages
  • ISBN978-3-0365-3983-6 (Hardback)
  • ISBN978-3-0365-3984-3 (PDF)

This is a Reprint of the Special Issue Data Science in Healthcare that was published in

Environmental & Earth Sciences
Medicine & Pharmacology
Public Health & Healthcare
Summary

Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management.

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