5 citations · 7 across the 8 of their papers we have counts for
9 papers
CG-Probes: Recovering Guardrail Directions from Patient Query Embeddings
Marko Řeháček, Vítězslav Dušek, Martin Rusinko +1
Patient-facing AI assistants promise valuable support to patients, but incoming queries can pose medical risks. To create guardrails, we work with oncologists to define three ordin…
Computing patient similarity based on unstructured clinical notes
Petr Zelina, Marko Řeháček, Jana Halámková +3
Clinical notes hold rich yet unstructured details about diagnoses, treatments, and outcomes that are vital to precision medicine but hard to exploit at scale. We introduce a method…
Evaluating Open-Weight Large Language Models for Structured Data Extraction from Narrative Medical Reports Across Multiple Use Cases and Languages
Douwe J. Spaanderman, Karthik Prathaban, Petr Zelina +20
Large language models (LLMs) are increasingly used to extract structured information from free-text clinical records, but prior work often focuses on single tasks, limited models,…
Unsupervised extraction, labelling and clustering of segments from clinical notes
Petr Zelina, Jana Halámková, Vít Nováček
This work is motivated by the scarcity of tools for accurate, unsupervised information extraction from unstructured clinical notes in computationally underrepresented languages, su…
Finding Explanations of Entity Relatedness in Graphs: A Survey
Raoul Biagioni, Pierre-Yves Vandenbussche, Vit Novacek
Analysing and explaining relationships between entities in a graph is a fundamental problem associated with many practical applications. For example, a graph of biological pathways…
Formalising Hypothesis Virtues in Knowledge Graphs: A General Theoretical Framework and its Validation in Literature-Based Discovery Experiments
Vit Novacek
We introduce an approach to discovery informatics that uses so called knowledge graphs as the essential representation structure. Knowledge graph is an umbrella term that subsumes…
A Methodology for Empirical Analysis of LOD Datasets
Vit Novacek
CoCoE stands for Complexity, Coherence and Entropy, and presents an extensible methodology for empirical analysis of Linked Open Data (i.e., RDF graphs). CoCoE can offer answers to…
Technical report: Linking the scientific and clinical data with KI2NA-LHC
Vit Novacek, Aisha Naseer
We introduce a use case and propose a system for data and knowledge integration in life sciences. In particular, we focus on linking clinical resources (electronic patient records)…
Distributional Framework for Emergent Knowledge Acquisition and its Application to Automated Document Annotation
Vit Novacek
The paper introduces a framework for representation and acquisition of knowledge emerging from large samples of textual data. We utilise a tensor-based, distributional representati…