Related Experiment Video For Artificial intelligence
Updated: Aug 6, 2026
Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules
Published on: October 13, 2023
Improving follow-up of incidental pulmonary nodules in the emergency department using an artificial
Peter P Olivieri1, Anika Markan2, Darwin Ashbaker1
1Department of Medicine, Sub-Department of Pulmonary and Critical Care, University of Maryland Baltimore Washington Medical Center, 301 Hospital Drive, Second Floor, Glen Burnie, MD, 21061, United States.
Background:
Incidental pulmonary nodules (IPNs) are frequently identified on computed tomography (CT) scans but are often associated with poor rates of patient notification and follow-up, limiting opportunities for early lung cancer detection.
Objective:
To evaluate whether implementation of an artificial intelligence (AI)-supported workflow improves patient notification and follow-up of IPNs detected in the emergency department (ED).
Methods:
We conducted a retrospective pre-post cohort study at an academic-affiliated community hospital. The pre-intervention cohort included ED patients undergoing chest CT between January and March 2023. The post-intervention cohort included ED patients undergoing chest CT between June and August 2025, in which an AI-based natural language processing system identified potential IPNs from radiology reports, and patients were contacted to facilitate follow-up. Primary outcomes were rates of patient notification about their IPN and nodule-specific follow-up.
Results:
With implementation of the AI-supported workflow, patient notification increased from 171/228 (75%) to 223/252 (88.4%) p = 0.0001, and nodule-specific follow-up increased from 122/228 (53.5%) to 171/252 (67.9%) p = 0.0012. Inability to reach patients by phone after their ED visit was identified as a significant barrier to follow-up. There was no significant difference in lung cancer stage at diagnosis between cohorts.
Conclusions:
An AI-supported IPN identification and outreach workflow improved patient notification and follow-up. Proactive communication strategies, facilitated by AI, represent a feasible approach to addressing care gaps and enhancing early lung cancer detection.
