Data science and medical informatics in healthcare technologies /

Data science and medical informatics in healthcare technologies /

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Bibliographic Details
Author / Creator:	Linh, Nguyen Thi Dieu.
Imprint:	Singapore : Springer, 2021.
Description:	1 online resource
Language:	English
Series:	SpringerBriefs in applied sciences and technology, Forensic and medical bioinformatics, 2196-8845 SpringerBriefs in applied sciences and technology. Forensic and medical bioinformatics,
Subject:	Medical informatics. Bioinformatics. Bioinformatics. Medical informatics.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12613344

Hidden Bibliographic Details
Other authors / contributors:	Lu, Zhongyu, 1955- author.
ISBN:	9789811630293 9811630291 9811630283 9789811630286
Notes:	Includes bibliographical references. Online resource; title from PDF title page (SpringerLink, viewed June 28, 2021).
Summary:	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.
Other form:	Original 9811630283 9789811630286
Standard no.:	10.1007/978-981-16-3029-3

Table of Contents:

1. A Value of Data Science in the Medical Informatics: An Overview
2. Data science in Medical Informatics: Challenges and Opportunities
3. Eminent Role of Machine Learning in the Healthcare Data Management
4. Potential and Adoption of Data Science in the Healthcare Analytics
5. Emerging Advancement of Data Science in the Healthcare Informatics.