Condition: Pulmonary Fibrosis · Sponsor: University of California, Los Angeles
This study is a prospective observational study for subjects with idiopathic pulmonary fibrosis (IPF) or non-IPF interstitial lung diseases (ILD). The purpose of this study is to compare whether imaging patterns from high-resolution computed tomography (HRCT) at baseline can predict worsening. Single Time point Prediction (STP) is a score derived from an artificial intelligenc/ machine learning (AI/ML) using the radiomic features from a HRCT scan that quantifies the imaging patterns of short-term predictive worsening.
This description comes directly from the study's public registry record.
Grace Hyun Kim, PhD · (310) 481-7594 · GraceKim@mednet.ucla.edu
Claudia L Perdomo, AS · 310-267-4707 · cperdomo@mednet.ucla.edu
Always discuss trial participation with your own doctor first.
| UCLA | Los Angeles, California, United States | Recruiting |
Get one email when the public record changes — results posted, or the study's status changes. Nothing else, ever.
We email about this public record only. Unsubscribe anytime with one click. Never medical advice.
This page is independently generated by Eichor from the public ClinicalTrials.gov record and re-synced daily. It is not the sponsor's official website unless claimed. Nothing here is medical advice; eligibility is always determined by the study team — talk to your own doctor first.
Source record: clinicaltrials.gov/study/NCT06162884