4 papers
Learning temporal embeddings from electronic health records of chronic kidney disease patients
Aditya Kumar, Mario A. Cypko, Oliver Amft
We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations without compromising predictive p…
Temporal Fusion Nexus: A task-agnostic multi-modal embedding model for clinical narratives and irregular time series in post-kidney transplant care
Aditya Kumar, Simon Rauch, Mario Cypko +10
We introduce Temporal Fusion Nexus (TFN), a multi-modal and task-agnostic embedding model to integrate irregular time series and unstructured clinical narratives. We analysed TFN i…
Med-gte-hybrid: A contextual embedding transformer model for extracting actionable information from clinical texts
Aditya Kumar, Simon Rauch, Mario Cypko +1
We introduce a novel contextual embedding model med-gte-hybrid that was derived from the gte-large sentence transformer to extract information from unstructured clinical narratives…
Enhancing Productivity in Database Management Through AI: A Three-Phase Approach for Database
Kushagra Parashar, Ajay Dev, Aditya Kumar +1
This paper presents a novel AI-powered framework designed to streamline database management and query optimization for PostgreSQL systems. Structured in three phases: Natural Langu…