3 citations · 3 across the 3 of their papers we have counts for
5 papers
How sensitive do we want AI to be? Socio-communicative competencies of large language models in healthcare
Dorothee Amelung, Andrew M. Bean, Sabine C. Herpertz +4
Background. Effective clinical practice relies heavily on the socio-communicative skills of medical professionals. Large language models (LLMs) have been proposed for tasks such as…
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…
Multimodal deep learning approach to predicting neurological recovery from coma after cardiac arrest
Felix H. Krones, Ben Walker, Guy Parsons +2
This work showcases our team's (The BEEGees) contributions to the 2023 George B. Moody PhysioNet Challenge. The aim was to predict neurological recovery from coma following cardiac…
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…
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…