Pulmonary Embolism Survival Prediction Using Multimodal Learning Based on Computed Tomography Angiography and Clinical Data
Multiomic DL models incorporating CTPA features, clinical data, and PESI achieved higher c-indices than PESI alone for PE survival prediction.
Authors
- Colin F. Greineder (ORCID: https://orcid.org/0000-0001-9740-7672)
- Zhusi Zhong (ORCID: https://orcid.org/0009-0008-5371-1443)
- John Sollee (ORCID: https://orcid.org/0000-0002-8066-4418)
- Cheng Ting Lin (ORCID: https://orcid.org/0000-0003-0275-8037)
- Scott Collins (ORCID: https://orcid.org/0000-0002-8117-164X)
- Zhicheng Jiao (ORCID: https://orcid.org/0000-0002-6968-0919)
- Fayez H. Fayad (ORCID: https://orcid.org/0000-0003-4074-0321)
- Michael K. Atalay (ORCID: https://orcid.org/0000-0003-3549-2634)
- Jie Li (ORCID: https://orcid.org/0000-0001-7950-4233)
- Helen Zhang (ORCID: https://orcid.org/0000-0003-1023-0646)
- Shreyas Kulkarni (ORCID: https://orcid.org/0000-0002-6723-515X)
- Xinbo Gao (ORCID: https://orcid.org/0000-0003-1443-0776)
- Harrison X. Bai (ORCID: https://orcid.org/0000-0002-9614-2163)
- Sun Ho Ahn (ORCID: https://orcid.org/0009-0000-3043-5222)
- Andrew C. Lancaster
Institutions
- Johns Hopkins University (US)
- Xidian University (CN)
- Brown University (US)
- University of Michigan (US)
- Johns Hopkins Medicine (US)
- Rhode Island Hospital (US)
Publication Details
- Journal
- Journal of Thoracic Imaging
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1097/rti.0000000000000831
- Citations
- 3
- Primary Topic
- Venous Thromboembolism Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 5.61