A Patient Home Lung Disease Self Check System Using Datasets and Artificial Intelligence
Principal Investigator
Name
Bao Yuanjin
Degrees
M.S
Institution
Hangzhou University of Electronic Science and Technology
Position Title
Grauate Student
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1281
Initial CDAS Request Approval
Jul 8, 2024
Title
A Patient Home Lung Disease Self Check System Using Datasets and Artificial Intelligence
Summary
This project aims to enable patients to diagnose when they should go to the hospital for treatment at home without having to ask doctors online or check diagnostic books themselves. It attempts to build a bridge between artificial intelligence technology and personalized medical services. We can use the dataset to run AI for diagnosis, during which we can manually set some judgment threshold standards (or fuzzy logic threshold standards) to assist in judgment. By leveraging the power of machine learning, building models can help determine whether the subjects are at risk of developing lung disease and lung cancer.
Aims
Developing AI models, combining insights from CT image data analysis with clinical data, to improve the diagnostic accuracy of lung disease.
Enable patients to achieve initial and accurate diagnosis of lung cancer at home without relying on manual interpretation by doctors.
Compared with traditional doctor diagnosis, the advantages of artificial intelligence deep learning models in diagnosing lung diseases have been verified.
Collaborators
Doctor，Southeast University，Jifei Tang