papers

Publications (5)

cs.CL2024

Do Large Language Models have Shared Weaknesses in Medical Question Answering?

Andrew M. Bean, Karolina Korgul, Felix Krones +2

Large language models (LLMs) have made rapid improvement on medical benchmarks, but their unreliability remains a persistent challenge for safe real-world uses. To design for the u…

cs.LG2024

Combining Hough Transform and Deep Learning Approaches to Reconstruct ECG Signals From Printouts

Felix Krones, Ben Walker, Terry Lyons +1

This work presents our team's (SignalSavants) winning contribution to the 2024 George B. Moody PhysioNet Challenge. The Challenge had two goals: reconstruct ECG signals from printo…

cs.LG2023

Dual Bayesian ResNet: A Deep Learning Approach to Heart Murmur Detection

Benjamin Walker, Felix Krones, Ivan Kiskin +3

This study presents our team PathToMyHeart's contribution to the George B. Moody PhysioNet Challenge 2022. Two models are implemented. The first model is a Dual Bayesian ResNet (DB…

cs.LG2024

Review of multimodal machine learning approaches in healthcare

Felix Krones, Umar Marikkar, Guy Parsons +2

Machine learning methods in healthcare have traditionally focused on using data from a single modality, limiting their ability to effectively replicate the clinical practice of int…

cs.CV2026

From pre-training to downstream performance: Does domain-specific pre-training make sense?

Felix Krones

Deep learning techniques have revolutionised medical imaging, improving diagnostic accuracy and enabling both more accurate and earlier disease detection. However, the relationship…