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cs.CV2024

RadPhi-3: Small Language Models for Radiology

Mercy Ranjit, Shaury Srivastav, Tanuja Ganu

LLM based copilot assistants are useful in everyday tasks. There is a proliferation in the exploration of AI assistant use cases to support radiology workflows in a reliable manner…

cs.CV2024

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

Harshita Sharma, Valentina Salvatelli, Shaury Srivastav +13

There is growing interest in applying AI to radiology report generation, particularly for chest X-rays (CXRs). This paper investigates whether incorporating pixel-level information…

cs.CL2024

MAIRA-2: Grounded Radiology Report Generation

Shruthi Bannur, Kenza Bouzid, Daniel C. Castro +18

Radiology reporting is a complex task requiring detailed medical image understanding and precise language generation, for which generative multimodal models offer a promising solut…

cs.HC2024

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Anja Thieme, Abhijith Rajamohan, Benjamin Cooper +22

Nasogastric tubes (NGTs) are feeding tubes that are inserted through the nose into the stomach to deliver nutrition or medication. If not placed correctly, they can cause serious h…

cs.CL2024

MAIRA-1: A specialised large multimodal model for radiology report generation

Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid +12

We present a radiology-specific multimodal model for the task for generating radiological reports from chest X-rays (CXRs). Our work builds on the idea that large language model(s)…

cs.CL2024

RAD-PHI2: Instruction Tuning PHI-2 for Radiology

Mercy Ranjit, Gopinath Ganapathy, Shaury Srivastav +2

Small Language Models (SLMs) have shown remarkable performance in general domain language understanding, reasoning and coding tasks, but their capabilities in the medical domain, p…