8 citations · 10 across the 4 of their papers we have counts for
5 papers · 1 filter
PARROT: An Open Multilingual Radiology Reports Dataset
Bastien Le Guellec, Kokou Adambounou, Lisa C Adams +85
Rationale and Objectives: To develop and validate PARROT (Polyglottal Annotated Radiology Reports for Open Testing), a large, multicentric, open-access dataset of fictional radiolo…
Multi-step retrieval and reasoning improves radiology question answering with large language models
Sebastian Wind, Jeta Sopa, Daniel Truhn +9
Clinical decision-making in radiology increasingly benefits from artificial intelligence (AI), particularly through large language models (LLMs). However, traditional retrieval-aug…
Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs
Juraj Vladika, Annika Domres, Mai Nguyen +10
Large language models (LLMs) exhibit extensive medical knowledge but are prone to hallucinations and inaccurate citations, which pose a challenge to their clinical adoption and reg…
Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors
Jacqueline Lammert, Nicole Pfarr, Leonid Kuligin +16
Rare gynecological tumors (RGTs) present major clinical challenges due to their low incidence and heterogeneity. The lack of clear guidelines leads to suboptimal management and poo…
Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data
Felix J. Dorfner, Amin Dada, Felix Busch +8
Large language models (LLMs) have shown potential in biomedical applications, leading to efforts to fine-tune them on domain-specific data. However, the effectiveness of this appro…