Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/31947
Title: Various cancer analysis using big data analysis technology-An advanced approach
Authors: Mishra, Ayush Chandra
Chaubey, Ratnesh
Ojha, Smriti
Mishra, Sudhanshu
Sekar, Mahendran
Verma, Swati
(UniKL RCMP)
Keywords: Big Data
Cancer
Clinical Rill Stratification
Computational Approach
Datasets
Disease
Predictive Analysis
Issue Date: Aug-2023
Publisher: River Publishers
Citation: Big data in Oncology: impact, challenges, and risk assessment. (2023, December 30). https://www.riverpublishers.com/book_details.php?book_id=1062
Abstract: In this modern era, big data provides an enormous amount of collected data about various diseases in India and throughout the world, which is created by data available in vast diversity, high speed, and volume. Because such data is becoming more prevalent, methods for handling and extracting insights from it must be studied and provided. Furthermore, decision-makers should be able to retrieve important from such a distinct, diverse, and frequently changing dataset, which encompasses everything from ordinary transactions to customer/patient interactions, as well as social media sites and other digital platforms. Big data is viewed as a revolution with the potential to change the way businesses function in a variety of industries. This study investigates the research data available from existing challenges and cases and applies big data analytics to enhance cancer risk categorization. We have divided the input data into three categories: pathology, radiomics, and population health management. Big data provides computational methodologies which will improve clinical risk stratification for cancer patients in a minimum period.
URI: https://www.riverpublishers.com/book_details.php?book_id=1062
https://ir.unikl.edu.my/jspui/handle/123456789/31947
ISBN: 9788770228121
ISSN: 9788770228138
Appears in Collections:Journal Articles

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