Paper Info
Title
Intelligent Perioperative System: Towards Real-time Big Data Analytics in Surgery Risk Assessment.
Abstract
Surgery risk assessment is an effective tool for physicians to manage the treatment of patients, but most current research projects fall short in providing a comprehensive platform to evaluate the patients' surgery risk in terms of different complications. The recent evolution of big data analysis techniques makes it possible to develop a real-time platform to dynamically analyze the surgery risk from large-scale patients information. In this paper, we propose the Intelligent Perioperative System (IPS), a real-time system that assesses the risk of postoperative complications (PC) and dynamically interacts with physicians to improve the predictive results. In order to process large volume patients data in real-time, we design the system by integrating several big data computing and storage frameworks with the high through-output streaming data processing components. We also implement a system prototype along with the visualization results to show the feasibility of system design.
Year
DOI
Venue
2017
10.1109/DASC-PICom-DataCom-CyberSciTec.2017.201
DASC/PiCom/DataCom/CyberSciTech
Keywords
DocType
Volume
Big data analysis,Perioprative risk prediction,Precision medicine,Real-time processing
Conference
abs/1709.10192
Citations 
PageRank 
References 
0
0.34
6
Authors
7
Name
Order
Citations
PageRank
Zheng Feng100.34
Rajendra Rana Bhat200.34
Xiaoyong Yuan31087.82
Daniel Freeman400.34
Tezcan Baslanti500.34
Azra Bihorac6508.63
Xiaolin Li724317.57