Hospital Mortality prediction

Principal Investigator

Name
Khoi Pham

Degrees
MoS Computer Science

Institution
CSUSB

Position Title
Grad Student

Email
minhkhoi89vn@yahoo.com

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.

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.