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Automatic medical report generation (MRG), which possesses significant research value as it can aid radiologists in clinical diagnosis and report composition, has garnered increasing attention.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Banerjee Satanjeev · 2005
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Difficulties in the interpretation of chest radiography. in: Comparative interpretation of ct and standard radiography of the chest
Louke Delrue, Robert Gosselin, Bart Ilsen, AVan Landeghem, Philippe Duyck, and JohanDe Mey · 2011
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Understanding what we see: how we derive meaning from vision
Alex Clarke and Lorraine K Tyler · 2015
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Recurrent topic-transition gan for visual paragraph generation
Xiaodan Liang, Zhiting Hu, Hao Zhang, Chuang Gan, and Eric P. Xing · 2017
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Bottom-up and top-down attention for image captioning and vqa
Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, StephenJ. Gould, and Lei Zhang · 2017
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Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers · 2017
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On the automatic generation of medical imaging reports
Baoyu Jing, Pengtao Xie, and Eric Xing · 2018
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi · 2019
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Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs, 2019
Alistair E. W. Johnson, Tom J. Pollard, Nathaniel R. Greenbaum, Matthew P. Lungren, Chih ying Deng, Yifan Peng, Zhiyong Lu, Roger G. Mark, Seth J. Berkowitz, and Steven Horng · 2019
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When radiology report generation meets knowledge graph
Yixiao Zhang, Xiaosong Wang, Ziyue Xu, Qihang Yu, AlanL. Yuille, and Daguang Xu · 2020
Earlier work this paper cites.
Generating radiology reports via memory-driven transformer
Zhihong Chen, Yan Song, Tsung-Hui Chang, and Xiang Wan · 2020
Cited alongside, same era.
Contrastive attention for automatic chest x-ray report generation
Fenglin Liu, Changchang Yin, Xian Wang, Shen Ge, Ping Zhang, and Xu Sun · 2021
Cited alongside, same era.
Exploring and distilling posterior and prior knowledge for radiology report generation
Fenglin Liu, Xian Wu, Shen Ge, Wei Fan, and Yuexian Zou · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision, 2021
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
Cited alongside, same era.
Clinical-bert: Vision-language pre-training for radiograph diagnosis and reports generation
Bin Yan and Mingtao Pei · 2022
Cited alongside, same era.
mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration
Qinghao Ye, Haiyang Xu, Jiabo Ye, Ming Yan, Haowei Liu, Qi Qian, Ji Zhang, Fei Huang, and Jingren Zhou · 2023
Later among the works it cites.
Promptmrg: Diagnosis-driven prompts for medical report generation
Haibo Jin, Haoxuan Che, Yi Lin, and Hao Chen · 2024
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Mitigating fine-grained hallucination by fine-tuning large vision-language models with caption rewrites
Lei Wang, Jiabang He, Shenshen Li, Ning Liu, and Ee-Peng Lim · 2024
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Improving clip training with language rewrites
Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, and Yonglong Tian · 2024
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Miss: A generative pretraining and finetuning approach for med-vqa
Jiawei Chen, Dingkang Yang, Yue Jiang, et al · 2024
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou · 2022
Cited alongside, same era.
Mitigating hallucination in visual language models with visual supervision
Zhiyang Chen, Yousong Zhu, Yufei Zhan, Zhaowen Li, Chaoyang Zhao, Jinqiao Wang, and Ming Tang · 2023
Cited alongside, same era.
GPT-4V(vision) system card
Openai, 2023 · 2023
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Llava-med: Training a large language-and-vision assistant for biomedicine in one day
Chunyuan Li, Cliff Wong, Zhang, et al · 2023
Cited alongside, same era.
Minigpt-4: Enhancing vision-language understanding with advanced large language models
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny · 2023
Cited alongside, same era.
Xraygpt: Chest radiographs summarization using medical vision-language models
Omkar Thawkar, Abdelrahman Shaker, Sahal Shaji Mullappilly, Hisham Cholakkal, Rao Muhammad Anwer, Salman Khan, Jorma Laaksonen, and Fahad Shahbaz Khan · 2023
Cited alongside, same era.
Automated radiographic report generation purely on transformer: A multi-criteria supervised approach
Zhanyu Wang, Hongwei Han, Lei Wang, and Luping Zhou
Cited in the paper.
Cod, towards an interpretable medical agent using chain of diagnosis, 2024
Junying Chen, Chi Gui, Anningzhe Gao, Ke Ji, Xidong Wang, Xiang Wan, and Benyou Wang · 2024
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Enhancing depression diagnosis with chain-of-thought prompting
Elysia Shi, Adithri Manda, London Chowdhury, Runeema Arun, Kevin Zhu, and Michael Lam · 2024
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Detecting and evaluating medical hallucinations in large vision language models, 2024
Jiawei Chen, Dingkang Yang, et al · 2024
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Gemini: A family of highly capable multimodal models, 2024
Gemini Team Google · 2024
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Contextual feature extraction hierarchies converge in large language models and the brain
Mischler, Gavin and Li, Yinghao Aaron and Bickel, Stephan and Mehta, Ashesh D and Mesgarani, Nima · 2024
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