Vision-language model for report generation and outcome prediction in CT pulmonary angiogram

Vision-language model for report generation and outcome prediction in CT pulmonary angiogram

Abstract Accurate and comprehensive interpretation of pulmonary embolism (PE) from Computed Tomography Pulmonary Angiography (CTPA) scans remains a clinical challenge due to the limited specificity and structure of existing AI tools. We propose an agent-based framework that integrates Vision-Languag...

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Main Authors: Zhusi Zhong, Yuli Wang, Jing Wu, Wen-Chi Hsu, Vin Somasundaram, Lulu Bi, Shreyas Kulkarni, Zhuoqi Ma, Scott Collins, Grayson Baird, Sun Ho Ahn, Xue Feng, Ihab Kamel, Cheng Ting Lin, Colin Greineder, Michael Atalay, Zhicheng Jiao, Harrison Bai
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01807-8
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https://doi.org/10.1038/s41746-025-01807-8

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