Welcome

The DSAIG seminar series aim to bring together faculty members and students across different disciplines within the University to discuss research topics that are related to Data Science and its applications. It serves as a forum to foster interdisciplinary research and to uncover new possibilities for research collaboration in the Data Science field.

Monthly seminars will be organized with focuses on specific research topics related to Data Science and its applications, and given by renowned experts of the field with a broad range of academic backgrounds including Business, Engineering, Science, and Social Science.

For enquiries, please contact us at cb-dsaig@cityu.edu.hk.


Next Seminar

By Dr. Kevin SUN

Mining Triage Notes to Predict Emergency Department Admissions

By Dr. Kevin SUN

Date
11 October 2017 (Wednesday)
Time
12:30pm-2:00pm
Venue
Room 14-221, 14/F, Lau Ming Wai Academic Building (AC3), City University of Hong Kong
Language
English
Registration
Register Here

(A light sandwich lunch will be provided starting from 12:00noon. Please confirm your attendance.)

 

Abstract
Emergency department (ED) overcrowding is a worldwide problem that undermines hospitals’ ability to provide timely care to patients who need it urgently. One of the primary reason for ED overcrowding is long ED boarding time due to the lack of coordination between ED and inpatient units. The objectives of this study were to develop models that use patient information collected during triage at EDs to predict the inpatient admission decisions, and to test how the information derived from free-text triage notes by text mining can increase the prediction power. We developed a Lasso Logistic regression model to predict the admission decision for an individual patient using the patient information collected during triage. Such predictive information can potentially reduce ED boarding time by initiating early admission process. Text mining techniques are applied to extract useful information from the free-text triage notes. Our study demonstrated that statistical models can predict ED patient admissions with reasonable accuracy using the routine patient data collected during triage: c-statistics 0.862 (95% CI: 0.857-0.867). Text mining can extract additional useful information from triage notes and significantly increase the prediction power. With the predictive information available in advance, hospitals can be proactive on the admission process, discharge process and bed allocations so as to reduce ED overcrowding.

Biography
Dr. Zhankun (Kevin) Sun is an Assistant Professor of Management Sciences in the College of Business, City University of Hong Kong. He holds a bachelor degree in Industrial Engineering from Tsinghua University, an M.Sc. and a Ph.D. in Statistics and Operations Research from the University of North Carolina Chapel Hill. He is interested in the research area of modeling, analysis, and control of stochastic systems with applications that arise from healthcare operations. He is a recipient of George E. Nicholson Award from Department of Statistics & Operations Research at UNC Chapel Hill.


Forthcoming

Mining Triage Notes to Predict Emergency Department Admissions
By Dr. Kevin SUN
Emergency department (ED) overcrowding is a worldwide problem that undermines hospitals’ ability to provide timely care to patients who need it urgently. One of the ... [ more ]
 
Neurodynamics-based Parallel Data Selection in the Era of Big Data
By Jun WANG
In the present information era, huge amount of data to be processed daily. In contrast of conventional sequential data processing techniques, parallel data processing approaches can expedite the processes and more efficiently deal with big data. In... [ more ]
 
A Lightening Introduction to Parallel Computing: Using Apache Spark as an Example
By Zhenzhen WANG
Traditionally, many problems are so large and/or complex that it is impossible to solve them on a single computer, especially given limited computer ... [ more ]
 
Status Leaders, Hubs and their Social Influence
By Huazhong ZHAO
The prevalence of internet technology and social media has provided marketers new opportunities to identify influencers and utilize their social influence to affect consumer decisions. We introduce status leaders ... [ more ]
 
Development of two consumer satisfaction and confidence indexes
By Geoffrey TSO
We shall cover the development of two consumer indexes with local impacts in Hong Kong. The Hong Kong Consumer Satisfaction Index (HKCSI) is a leading performance indicator for HK businesses, measuring ... [ more ]
 
A Data-driven Approach to the Integrated Elderly Care
By Prof. Frank CHEN & Dr. Eman LEUNG
The global trend today is to shift the care burden away from the acute care and long-term care, which are costly and afford a poor quality of life, to community care and primary care, which are more conducive to active aging, more cost-effective and afford a higher quality of life... [ more ]
 

Previous

Prediction of chronic disease occurrence using EHR data: A pilot study in Hong Kong
By Dr. Qingpeng ZHANG
Chronic diseases are major causes of morbidity and mortality worldwide. Many chronic diseases are preventable through effective disease management and prevention programs. In addition, some... [ more ]
 
Mining Time Information in Digital Data
By Prof. Jonathan ZHU
Time is the single common denominator across all types of digital data from the internet, mobile networks, and IoT (internet of things). However, the rich information embedded in timestamps of digital data has often been taken for granted. As such, this gold... [ more ]
 
Understanding Demand Uncertainty
By Prof. Jeff HONG
Poisson processes are often used to model arrival (demand) processes in many business and engineering fields. In this talk, I will show you the results from a sequence of studies that we have done trying to understand the uncertainty behaviors in demand processes. The examples include phone calls... [ more ]
 
Blockchain as Trust Platform for Cross-boundary Dataflow
By Prof. Leon ZHAO
In the era of big data, more and more companies have become digitized. Further, under globalization initiatives such as the One-Belt One Road effort, business processes are being automated nowadays cross companies, leading to cross-boundary data flow. However, conventional information... [ more ]
 
 

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