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Data Science and Medical Informatics in Healthcare Technologies - Nguyen Thi Dieu Linh - Bog

Bag om Data Science and Medical Informatics in Healthcare Technologies

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789811630316
  • Indbinding:
  • Paperback
  • Sideantal:
  • 86
  • Udgivet:
  • 24. juli 2021
  • Udgave:
  • 12021
  • Størrelse:
  • 155x235x0 mm.
  • Vægt:
  • 163 g.
  • 8-11 hverdage.
  • 16. januar 2025
Forlænget returret til d. 31. januar 2025
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Beskrivelse af Data Science and Medical Informatics in Healthcare Technologies

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.

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