Deep Learning Model to Predict the Recurrence of Stage IA Invasive Lung Adenocarcinoma After Sub-lobar Resection

Brief summary (registry, in English)

This study aims to develop a deep learning model based on noncontrast CT images to predict the recurrence risk of stage IA invasive lung adenocarcinoma after sub-lobar resection，which can serve as potential tool to assist thoracic surgeons in making optimal treatment decisions.The study will use existing CT data to train and validate the model, without requiring any additional intervention for the participants.

What you commit to

• Study type: Observational
• Participants enrolled: 9
• From 1 Jun 2023 to the primary completion date, 1 Jan 2024
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Who the study is looking for

Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

Sites (1)

Sites in registry order. Pick your city on the disease page to sort them by distance.