Developing AI-based diagnostic system for lung cancer through joint business plan

Principal Investigator

Name
Taegyu Kim

Degrees
Bachelor of Engineering

Institution
DEEPNOID

Position Title
Chief Technical Officer

Email
great@deepnoid.com

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-531

Initial CDAS Request Approval
Jun 24, 2019

Title
Developing AI-based diagnostic system for lung cancer through joint business plan

Summary
Lung cancer is one of the most common cancers in the world. If a lung nodule is detected in the earlier stages of lung cancer, the overall survival rate, which is 5 years, can increase. To come up with more treatment options, a fast and accurate diagnosis is needed. Artificial intelligence can provide a much-needed boost to doctors.
Our main goal is to improve efficiency of lung nodule detection with the help of artificial intelligence. Algorithms that we are studying contain automated 1) detection, 2) classification(GGN: Ground-glass nodule, Solid, None Solid, Calcification), 3) measurement(size and volume of nodule), and 4) nodule follow up(by comparing with the patient’s past CT films).

Aims

Lung nodule detection with a high level of sensitivity

Collaborators

Hwiyoung Kim, Department of Radiology, Severance Hospital, Yonsei University, Seoul, Korea