Development of clinically applied recurrence prediction model through artificial intelligence

Principal Investigator

Name
Sung Yong Kim

Degrees
M.S.

Institution
Infinitt Healthcare co,ltd

Position Title
Assistant Researcher

Email
sykim@infinitt.com

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-767

Initial CDAS Request Approval
Mar 10, 2021

Title
Development of clinically applied recurrence prediction model through artificial intelligence

Summary
Our study aims to develop a clinically applicable recurrence prediction model through clinical information and pathological imaging. When training the recurrence prediction algorithm models, we will use your data, including pathologic images and clinical information. In order to improve the accuracy of the recurrence prediction algorithm, it is evaluated and improved through the data set. We intend to extract and advance recurrence predictors through our algorithm.

Aims

1. Develop and evaluate the system that can segment to the tumor and other organ.
2. Develop and evaluate the system that can predict cancer recurrence.

Collaborators

Infinitt co,ltd
NCC(National Cancer Center) in korea