Earlier discharge from pulmonary nodule follow-up using artificial intelligence based volume measurements in computed tomography.
Journal:
European journal of radiology
Published Date:
Jun 17, 2025
Abstract
BACKGROUND: Lung cancer is the leading cause of cancer death worldwide. Effective screening and early detection are critical in reducing mortality. Artificial intelligence (AI) methods have been proved useful in the diagnosis of pulmonary nodules and early diagnosis of lung cancer. However, the implementation of lung cancer screening and frequent detection of incidental pulmonary nodules lead to more computed tomography scans resulting in increased costs. Therefore, determining the cost-effectiveness of AI is important for implementing these methods in routine clinical practice. Based on volume measurements of pulmonary nodules performed by AI, patients could potentially be discharged earlier from incidental lung nodule follow-up.
Authors
Keywords
Aged
Artificial Intelligence
Early Detection of Cancer
Female
Follow-Up Studies
Humans
Lung Neoplasms
Male
Middle Aged
Multiple Pulmonary Nodules
Patient Discharge
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Retrospective Studies
Sensitivity and Specificity
Solitary Pulmonary Nodule
Tomography, X-Ray Computed
