5 papers
Big, Bright, or Invisible: A Frozen-Feature Benchmark of 3D CT Foundation Models
Maulik Chevli, Johannes Brandt, Rickmer Braren +2
Routine CT interpretation is inherently comprehensive, capturing incidental findings across the entire scan volume. 3D CT foundation models could assist this process by providing g…
Echo2ECG: Enhancing ECG Representations with Cardiac Morphology from Multi-View Echos
Michelle Espranita Liman, Ãzgün Turgut, Alexander Müller +3
Electrocardiography (ECG) is a low-cost, widely used modality for diagnosing electrical abnormalities like atrial fibrillation by capturing the heart's electrical activity. However…
Multi-View Stenosis Classification Leveraging Transformer-Based Multiple-Instance Learning Using Real-World Clinical Data
Nikola Cenikj, Ãzgün Turgut, Alexander Müller +6
Coronary artery stenosis is a leading cause of cardiovascular disease, diagnosed by analyzing the coronary arteries from multiple angiography views. Although numerous deep-learning…
Benchmarking Uncertainty Calibration in Large Language Model Long-Form Question Answering
Philip Müller, Nicholas PopoviÄ, Michael Färber +1
Large Language Models (LLMs) are commonly used in Question Answering (QA) settings, increasingly in the natural sciences if not science at large. Reliable Uncertainty Quantificatio…
LungEvaty: A Scalable, Open-Source Transformer-based Deep Learning Model for Lung Cancer Risk Prediction in LDCT Screening
Johannes Brandt, Maulik Chevli, Rickmer Braren +3
Lung cancer risk estimation is gaining increasing importance as more countries introduce population-wide screening programs using low-dose CT (LDCT). As imaging volumes grow, scala…