3 papers
Explainable Machine Learning for Sepsis Outcome Prediction Using a Novel Romanian Electronic Health Record Dataset
Andrei-Alexandru Bunea, Ovidiu Ghibea, Dan-Matei Popovici +2
We develop and analyze explainable machine learning (ML) models for sepsis outcome prediction using a novel Electronic Health Record (EHR) dataset from 12,286 hospitalizations at a…
Querying Structured Data Through Natural Language Using Language Models
Hontan Valentin-Micu, Bunea Andrei-Alexandru, Tantaroudas Nikolaos Dimitrios +1
This paper presents an open source methodology for allowing users to query structured non textual datasets through natural language Unlike Retrieval Augmented Generation RAG which…
SegMate: Asymmetric Attention-Based Lightweight Architecture for Efficient Multi-Organ Segmentation
Andrei-Alexandru Bunea, Dan-Matei Popovici, Radu Tudor Ionescu
State-of-the-art models for medical image segmentation achieve excellent accuracy but require substantial computational resources, limiting deployment in resource-constrained clini…