Artificial Intelligence, Lung Nodule
Conditions
Brief summary
The current study aims to develop and validate a deep learning signature for diagnosing pathology and predicting prognosis of lung nodule using smartphone photos of resected tumor specimens.
Interventions
DIAGNOSTIC_TESTAI model
AI model developed by smartphone photos of resected tumor specimens
Sponsors
The First Affiliated Hospital of Soochow University
Ningbo No. 1 Hospital
Anhui Provincial Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
20 Years to 75 Years
Healthy volunteers
No
Inclusion criteria
(1) Participants scheduled for surgery for radiological finding of pulmonary lesions from the preoperative thin-section CT scans; (2) Age ranging from 20-75 years.
Exclusion criteria
(1) Participants with incomplete clinical information; (2) Participants who have received anti-tumor therapy.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Area under the receiver operating characteristic curve | From enrollment to the end of the study, assessed up to 6 months |
Countries
China
Contacts
Primary ContactYifan Zhong, PhD
Outcome results
None listed