10 papers
Calibrated Confidence Expression for Radiology Report Generation
David Bani-Harouni, Chantal Pellegrini, Julian Lüers +6
Safe deployment of Large Vision-Language Models (LVLMs) in radiology report generation requires not only accurate predictions but also clinically interpretable indicators of when o…
EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records
Chantal Pellegrini, Ege Ãzsoy, David Bani-Harouni +2
Forecasting how a patient's condition is likely to evolve, including possible deterioration, recovery, treatment needs, and care transitions, could support more proactive and perso…
Prototype-Based Knowledge Guidance for Fine-Grained Structured Radiology Reporting
Chantal Pellegrini, Adrian Delchev, Ege Ãzsoy +2
Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must make many fine-grained, discrete decis…
Language Agents for Hypothesis-driven Clinical Decision Making with Reinforcement Learning
David Bani-Harouni, Chantal Pellegrini, Ege Ãzsoy +2
Clinical decision-making is a dynamic, interactive, and cyclic process where doctors have to repeatedly decide on which clinical action to perform and consider newly uncovered info…
Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models
David Bani-Harouni, Chantal Pellegrini, Paul Stangel +4
A safe and trustworthy use of Large Language Models (LLMs) requires an accurate expression of confidence in their answers. We propose a novel Reinforcement Learning approach that a…
SpeechCT-CLIP: Distilling Text-Image Knowledge to Speech for Voice-Native Multimodal CT Analysis
Lukas Buess, Jan Geier, David Bani-Harouni +6
Spoken communication plays a central role in clinical workflows. In radiology, for example, most reports are created through dictation. Yet, nearly all medical AI systems rely excl…