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.

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.

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Holdings ( 1 )
Title notes ( 4 )

Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode	Item holds
Books	Faculty of CS & IT Library CS & IT Shelf No. 44 New Arrival	Book	610.285 LIN-D 2021 789576 (Browse shelf(Opens below))	C 1	Available		789576

Total holds: 0

Description based on print version record.

Includes bibliographical references.

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.