A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings

Abstract Large foundation models show promise in biomedicine but face challenges in clinical use due to performance gaps, accessibility, cost, and lack of scalable evaluation. Here we show that open-source small multimodal models can bridge these gaps in radiology by generating free-text findings fr...

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Váldodahkkit:	Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu, Naoto Usuyama, Sheng Zhang, Fei Wang, Yujia Xie, Mahmoud Khademi, Ziyi Yang, Hany Awadalla, Julia Gong, Houdong Hu, Jianwei Yang, Chunyuan Li, Jianfeng Gao, Yu Gu, Cliff Wong, Mu Wei, Tristan Naumann, Muhao Chen, Matthew P. Lungren, Akshay Chaudhari, Serena Yeung-Levy, Curtis P. Langlotz, Sheng Wang, Hoifung Poon
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	Nature Portfolio 2025-04-01
Ráidu:	Nature Communications
Liŋkkat:	https://doi.org/10.1038/s41467-025-58344-x
Fáddágilkorat:	Lasit fáddágilkoriid Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!

A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings

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