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- Title
Interstitial lung disease diagnosis and prognosis using an AI system integrating longitudinal data.
- Authors
Mei, Xueyan; Liu, Zelong; Singh, Ayushi; Lange, Marcia; Boddu, Priyanka; Gong, Jingqi Q. X.; Lee, Justine; DeMarco, Cody; Cao, Chendi; Platt, Samantha; Sivakumar, Ganesh; Gross, Benjamin; Huang, Mingqian; Masseaux, Joy; Dua, Sakshi; Bernheim, Adam; Chung, Michael; Deyer, Timothy; Jacobi, Adam; Padilla, Maria
- Abstract
For accurate diagnosis of interstitial lung disease (ILD), a consensus of radiologic, pathological, and clinical findings is vital. Management of ILD also requires thorough follow-up with computed tomography (CT) studies and lung function tests to assess disease progression, severity, and response to treatment. However, accurate classification of ILD subtypes can be challenging, especially for those not accustomed to reading chest CTs regularly. Dynamic models to predict patient survival rates based on longitudinal data are challenging to create due to disease complexity, variation, and irregular visit intervals. Here, we utilize RadImageNet pretrained models to diagnose five types of ILD with multimodal data and a transformer model to determine a patient's 3-year survival rate. When clinical history and associated CT scans are available, the proposed deep learning system can help clinicians diagnose and classify ILD patients and, importantly, dynamically predict disease progression and prognosis. Accurate diagnosis of interstitial lung disease subtypes and prediction of patient survival rates remains challenging. Here, the authors develop AI algorithms to combine patient's clinical history and longitudinal CT images to help clinicians diagnose and classify subtypes and dynamically predict disease progression and prognosis.
- Subjects
INTERSTITIAL lung diseases; PROGNOSIS; DIAGNOSIS; LUNGS; PANEL analysis; OVERALL survival; PROGRESSION-free survival
- Publication
Nature Communications, 2023, Vol 14, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-023-37720-5