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The release of ChatGPT, a language model capable of generating text that appears human-like and authentic, has gained significant attention beyond the research community. We expect that the convincing performance of ChatGPT incentivizes…

At the heart of radiological practice is the challenge of integrating complex imaging data with clinical information to produce actionable insights. Nuanced application of language is key for various activities, including managing requests,…

Large language models (LLMs) constitute a breakthrough state-of-the-art Artificial Intelligence technology which is rapidly evolving and promises to aid in medical diagnosis. However, the correctness and the accuracy of their returns has…

Computation and Language · Computer Science 2024-02-07 Dimitrios P. Panagoulias , Maria Virvou , George A. Tsihrintzis

This study introduces "RadCouncil," a multi-agent Large Language Model (LLM) framework designed to enhance the generation of impressions in radiology reports from the finding section. RadCouncil comprises three specialized agents: 1) a…

Computation and Language · Computer Science 2024-12-11 Fang Zeng , Zhiliang Lyu , Quanzheng Li , Xiang Li

Small Language Models (SLMs) have shown remarkable performance in general domain language understanding, reasoning and coding tasks, but their capabilities in the medical domain, particularly concerning radiology text, is less explored. In…

Computation and Language · Computer Science 2024-03-18 Mercy Ranjit , Gopinath Ganapathy , Shaury Srivastav , Tanuja Ganu , Srujana Oruganti

Radiology reports are often lengthy and unstructured, posing challenges for referring physicians to quickly identify critical imaging findings while increasing the risk of missed information. This retrospective study aimed to enhance…

Computation and Language · Computer Science 2025-06-05 Iryna Hartsock , Cyrillo Araujo , Les Folio , Ghulam Rasool

Large language models (LLMs) have demonstrated remarkable capabilities in various domains, including radiology report generation. Previous approaches have attempted to utilize multimodal LLMs for this task, enhancing their performance…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Wenjun Hou , Yi Cheng , Kaishuai Xu , Heng Li , Yan Hu , Wenjie Li , Jiang Liu

Healthcare systems around the world are grappling with issues like inefficient diagnostics, rising costs, and limited access to specialists. These problems often lead to delays in treatment and poor health outcomes. Most current AI and deep…

Artificial Intelligence · Computer Science 2025-12-22 Maliha Tabassum , M Shamim Kaiser

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among…

Computation and Language · Computer Science 2023-08-01 Hanyao Huang , Ou Zheng , Dongdong Wang , Jiayi Yin , Zijin Wang , Shengxuan Ding , Heng Yin , Chuan Xu , Renjie Yang , Qian Zheng , Bing Shi

Lab results are often confusing and hard to understand. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. We aim to assess the feasibility of using LLMs to generate…

Computation and Language · Computer Science 2024-04-23 Zhe He , Balu Bhasuran , Qiao Jin , Shubo Tian , Karim Hanna , Cindy Shavor , Lisbeth Garcia Arguello , Patrick Murray , Zhiyong Lu

Drafting radiology reports is a complex task requiring flexibility, where radiologists tail content to available information and particular clinical demands. However, most current radiology report generation (RRG) models are constrained to…

Computation and Language · Computer Science 2024-12-17 Zhuhao Wang , Yihua Sun , Zihan Li , Xuan Yang , Fang Chen , Hongen Liao

In clinics, a radiology report is crucial for guiding a patient's treatment. However, writing radiology reports is a heavy burden for radiologists. To this end, we present an automatic, multi-modal approach for report generation from a…

Image and Video Processing · Electrical Eng. & Systems 2022-06-02 Shuxin Yang , Xian Wu , Shen Ge , S. Kevin Zhou , Li Xiao

Writing radiology reports from medical images requires a high level of domain expertise. It is time-consuming even for trained radiologists and can be error-prone for inexperienced radiologists. It would be appealing to automate this task…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Yuzhe Lu , Sungmin Hong , Yash Shah , Panpan Xu

Medical report generation from imaging data remains a challenging task in clinical practice. While large language models (LLMs) show great promise in addressing this challenge, their effective integration with medical imaging data still…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Chunlei Li , Jingyang Hou , Yilei Shi , Jingliang Hu , Xiao Xiang Zhu , Lichao Mou

The escalating demand for medical image interpretation underscores the critical need for advanced artificial intelligence solutions to enhance the efficiency and accuracy of radiological diagnoses. This paper introduces CXR-PathFinder, a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Pimchanok Sukjai , Apiradee Boonmee

Social problems stemming from the shortage of radiologists are intensifying, and artificial intelligence is being highlighted as a potential solution. Recently emerging large-scale generative AI has expanded from large language models…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Inwoo Seo , Eunkyoung Bae , Joo-Young Jeon , Young-Sang Yoon , Jiho Cha

We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions. Because popular exams like AP Physics, LSAT, and GRE have large test-taker populations and ample test preparation…

Automated radiology report generation (RRG) aims to produce detailed textual reports from clinical imaging, such as computed tomography (CT) scans, to improve the accuracy and efficiency of diagnosis and provision of management advice. RRG…

Machine Learning · Computer Science 2025-07-03 Siyou Li , Pengyao Qin , Huanan Wu , Dong Nie , Arun J. Thirunavukarasu , Juntao Yu , Le Zhang

The emergence of Large Language Models (LLMs) presents unprecedented opportunities to revolutionize medical contrastive vision-language pre-training. In this paper, we show how LLMs can facilitate large-scale supervised pre-training,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Yingtai Li , Haoran Lai , Xiaoqian Zhou , Shuai Ming , Wenxin Ma , Wei Wei , Shaohua Kevin Zhou