14 citations · 15 across the 5 of their papers we have counts for
5 papers
Ascent: An Agentic System over the Model Context Protocol for Real-World Clinical Data Analysis
Angelo Ziletti, Leonardo D'Ambrosi, Melanie Tuchardt +1
Answering epidemiological questions from real-world clinical data requires medical coding, schema-aware SQL, and validation of implicit choices about populations, denominators, and…
Disentangling Ambiguity from Instability in Large Language Models: A Clinical Text-to-SQL Case Study
Angelo Ziletti, Leonardo D'Ambrosi
Deploying large language models for clinical Text-to-SQL requires distinguishing two qualitatively different causes of output diversity: (i) input ambiguity that should trigger cla…
Generating patient cohorts from electronic health records using two-step retrieval-augmented text-to-SQL generation
Angelo Ziletti, Leonardo D'Ambrosi
Clinical cohort definition is crucial for patient recruitment and observational studies, yet translating inclusion/exclusion criteria into SQL queries remains challenging and manua…
Fact Finder -- Enhancing Domain Expertise of Large Language Models by Incorporating Knowledge Graphs
Daniel Steinigen, Roman Teucher, Timm Heine Ruland +6
Recent advancements in Large Language Models (LLMs) have showcased their proficiency in answering natural language queries. However, their effectiveness is hindered by limited doma…
Retrieval augmented text-to-SQL generation for epidemiological question answering using electronic health records
Angelo Ziletti, Leonardo D'Ambrosi
Electronic health records (EHR) and claims data are rich sources of real-world data that reflect patient health status and healthcare utilization. Querying these databases to answe…