activity
20172024
most citedMultimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

78 citations · 102 across the 6 of their papers we have counts for

collaborators

6 papers

cs.HC202478 cited

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson, Maria T. Wetscherek +18

Recent advances in AI combine large language models (LLMs) with vision encoders that bring forward unprecedented technical capabilities to leverage for a wide range of healthcare a…

cs.CL20232 cited

Exploring the Boundaries of GPT-4 in Radiology

Qianchu Liu, Stephanie Hyland, Shruthi Bannur +16

The recent success of general-domain large language models (LLMs) has significantly changed the natural language processing paradigm towards a unified foundation model across domai…

cs.LG20233 cited

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging

Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro +3

As machine learning methods gain prominence within clinical decision-making, addressing fairness concerns becomes increasingly urgent. Despite considerable work dedicated to detect…

cs.CV20231 cited

Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query

Ho Hin Lee, Alberto Santamaria-Pang, Jameson Merkow +4

We introduce a novel Region-based contrastive pretraining for Medical Image Retrieval (RegionMIR) that demonstrates the feasibility of medical image retrieval with similar anatomic…

cs.CL2023

Compositional Zero-Shot Domain Transfer with Text-to-Text Models

Fangyu Liu, Qianchu Liu, Shruthi Bannur +9

Label scarcity is a bottleneck for improving task performance in specialised domains. We propose a novel compositional transfer learning framework (DoT5 - domain compositional zero…

q-bio.TO201718 cited

White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks

R. Guerrero, C. Qin, O. Oktay +8

The accurate assessment of White matter hyperintensities (WMH) burden is of crucial importance for epidemiological studies to determine association between WMHs, cognitive and clin…