Leveraging big data analytics in healthcare enhancement: trends, challenges and opportunities

A Rehman, S Naz, I Razzak - Multimedia Systems, 2022‏ - Springer
Clinical decisions are more promising and evidence-based, hence, big data analytics to
assist clinical decision-making has been expressed for a variety of clinical fields. Due to the …

Big data application in biomedical research and health care: a literature review

J Luo, M Wu, D Gopukumar… - Biomedical informatics …, 2016‏ - journals.sagepub.com
Big data technologies are increasingly used for biomedical and health-care informatics
research. Large amounts of biological and clinical data have been generated and collected …

How research in production and operations management may evolve in the era of big data

Q Feng, JG Shanthikumar - Production and Operations …, 2018‏ - journals.sagepub.com
We are living in an era in which data is generated in huge volume with high velocity and
variety. Big Data and technology are resha** our life and business. Our research …

Emergence of big data research in operations management, information systems, and healthcare: Past contributions and future roadmap

S Guha, S Kumar - Production and Operations Management, 2018‏ - journals.sagepub.com
In this day, in the age of big data, consumers leave an easily traceable digital footprint
whenever they visit a website online. Firms are interested in capturing the digital footprints of …

Industrial cyberphysical systems: Realizing cloud-based big data infrastructures

B Cheng, J Zhang, GP Hancke… - IEEE Industrial …, 2018‏ - ieeexplore.ieee.org
Future industrial systems and applications are expected to be complex constellations of
cyberphysical systems (CPSs) where intel l igent networked embedded devices play a …

Big Data in multiscale modelling: from medical image processing to personalized models

T Geroski, D Jakovljević, N Filipović - Journal of Big Data, 2023‏ - Springer
The healthcare industry is different from other industries–patient data are sensitive, their
storage needs to be handled with care and in compliance with regulative, while prediction …

Machine learning models for multidimensional clinical data

C Orphanidou, D Wong - Handbook of Large-Scale Distributed Computing …, 2017‏ - Springer
Healthcare monitoring systems in the hospital and at home generate large quantities of rich-
phenotype data from a wide array of sources. Typical sources include clinical observations …

Cloudwave: distributed processing of “Big Data” from electrophysiological recordings for epilepsy clinical research using Hadoop

CP Jayapandian, CH Chen, A Bozorgi… - AMIA Annual …, 2013‏ - pmc.ncbi.nlm.nih.gov
Epilepsy is the most common serious neurological disorder affecting 50–60 million persons
worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) …

A practice of TPC-DS multidimensional implementation on NoSQL database systems

H Zhao, X Ye - … and Benchmarking: 5th TPC Technology Conference …, 2014‏ - Springer
While NoSQL database systems are well established, it is not clear how to process
multidimensional OLAP queries on current key-value stores. In this paper, we detail how to …

An overview of online based platforms for sharing and analyzing electrophysiology data from big data perspective

Y Chen, Z Wang, G Yuan… - … Reviews: Data Mining and …, 2017‏ - Wiley Online Library
With the development of applications and high‐throughput sensor technologies in medical
fields, scientists and scientific professionals are facing a big challenge—how to manage and …