Validation of AI-Based Detection of Idiopathic Pulmonary Fibrosis in Serial Chest Radiographs: A Retrospective Longitudinal Study

VUNO Med-Chest X-ray · Не указано

ID реестра
NCT07712952
Фаза
Не указано
Статус
Завершено
Препарат / вмешательство
VUNO Med-Chest X-ray
Спонсор
Chung-Ang University Hospital
Набор участников
175
Центры
1

Об исследовании

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrotic lung disease of unknown cause with a median survival of only 3-5 years after diagnosis. Early detection and timely initiation of antifibrotic therapy may improve outcomes, but diagnosis is frequently delayed. Chest radiography (CXR) is widely accessible and cost-effective but has limited sensitivity for early interstitial opacity (IO), so radiologists may miss or delay documentation of relevant findings. This retrospective, single-center, observational cohort study evaluates whether an artificial-intelligence algorithm (VUNO Med-Chest X-ray) can detect interstitial opacity earlier than radiologists in the historical chest radiograph series of patients who were diagnosed with IPF. The cohort was identified via a April 2

Открыть NCT07712952 на ClinicalTrials.gov →

Медицинская оговорка. Эта страница обобщает публичные данные исследования NCT07712952 только для информации. Это не медицинская рекомендация, не одобрение и не предложение участия. Проверяйте детали на ClinicalTrials.gov и у квалифицированного врача.