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
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).
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