activity
20242026
most citedMedHELM: Holistic Evaluation of Large Language Models for Medical Tasks

10 citations · 16 across the 6 of their papers we have counts for

collaborators

9 papers

math.PR2026

A Probabilistic Generalization of the Mazur-Ulam Theorem

Justinas Zaliaduonis, Sergios Gatidis

The classical Mazur-Ulam theorem establishes that every surjective isometry between normed real vector spaces is an affine transformation. In various applied mathematical settings,…

cs.CV2025

MIMM-X: Disentangling Spurious Correlations for Medical Image Analysis

Louisa Fay, Hajer Reguigui, Bin Yang +2

Deep learning models can excel on medical tasks, yet often experience spurious correlations, known as shortcut learning, leading to poor generalization in new environments. Particu…

cs.CV2025

Retrospective motion correction in MRI using disentangled embeddings

Qi Wang, Veronika Ecker, Marcel Früh +2

Physiological motion can affect the diagnostic quality of magnetic resonance imaging (MRI). While various retrospective motion correction methods exist, many struggle to generalize…

cs.CL2025

Structuring Radiology Reports: Challenging LLMs with Lightweight Models

Johannes Moll, Louisa Fay, Asfandyar Azhar +5

Radiology reports are critical for clinical decision-making but often lack a standardized format, limiting both human interpretability and machine learning (ML) applications. While…

cs.CL202510 cited

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks

Suhana Bedi, Hejie Cui, Miguel Fuentes +78

While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinica…

cs.AI20251 cited

Adaptable Cardiovascular Disease Risk Prediction from Heterogeneous Data using Large Language Models

Frederike Lübeck, Jonas Wildberger, Frederik Träuble +4

Cardiovascular disease (CVD) risk prediction models are essential for identifying high-risk individuals and guiding preventive actions. However, existing models struggle with the c…