4 papers
No Data? No Problem: Robust Vision-Tabular Learning with Missing Values
Marta Hasny, Laura Daza, Keno Bressem +2
Large-scale medical biobanks provide imaging data complemented by extensive tabular information, such as clinical measurements or demographics. However, this abundance of tabular a…
Tables Guide Vision: Learning to See the Heart through Tabular Data
Marta Hasny, Maxime Di Folco, Keno Bressem +1
Contrastive learning methods in computer vision typically rely on augmented views of the same image or multimodal pretraining strategies that align paired modalities. However, thes…
Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis
Yousef Yeganeh, Azade Farshad, Ioannis Charisiadis +5
Scaling by training on large datasets has been shown to enhance the quality and fidelity of image generation and manipulation with diffusion models; however, such large datasets ar…
Semantic Alignment of Unimodal Medical Text and Vision Representations
Maxime Di Folco, Emily Chan, Marta Hasny +2
General-purpose AI models, particularly those designed for text and vision, demonstrate impressive versatility across a wide range of deep-learning tasks. However, they often under…