Hospital Mortality prediction
Principal Investigator
Name
Khoi Pham
Degrees
MoS Computer Science
Institution
CSUSB
Position Title
Grad Student
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-138
Initial CDAS Request Approval
May 11, 2015
Title
Hospital Mortality prediction
Summary
We want to build an Artificial Intelligent Agent System that can predict mortality rate and time occur base on given database and daily update patient information.
At this moment we may only focus on lung cancer patients' mortality. If there is a chance for mortality to occur, we will warn the hospital staffs who are authorized to be able to access to our system, so they can make early preparation for that patient.
At this moment we may only focus on lung cancer patients' mortality. If there is a chance for mortality to occur, we will warn the hospital staffs who are authorized to be able to access to our system, so they can make early preparation for that patient.
Aims
Our group in CSUSB Artificial Intelligent course want to build a Mortality Prediction Agent. The Agent will do data mining and deep learning, then make a decision how high the mortality is, before letting user know it. The warning message will also include reason, time prediction, improved treatment if possible.
We will use the NLST data on mortality, lung cancer, and risk factors to inform our Agent.
Collaborators
Tuan Nguyen, Essa Muharish, they're my group members.
Zhengping Wu , our professor in AI course.