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Found 7 papers, 4 papers with code
Hospitalization Length of Stay Prediction using Patient Event Sequences
Predicting patients hospital length of stay (LOS) is essential for improving resource allocation and supporting decision-making in healthcare organizations.
KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data Science
Hence, this paper presents a scalable platform, KGLiDS, that employs machine learning and knowledge graph technologies to abstract and capture the semantics of data science artifacts and their connections.
Simple and Powerful Architecture for Inductive Recommendation Using Knowledge Graph Convolutions
In this work, we propose SimpleRec, a strong baseline that uses a graph neural network and a KG to provide better recommendations than related inductive methods for new users and items.
Graph Neural Networks for Microbial Genome Recovery
In this paper, we propose to use Graph Neural Networks (GNNs) to leverage the assembly graph when learning contig representations for metagenomic binning.
Federated Data Science to Break Down Silos [Vision]
Similar to Open Data initiatives, data science as a community has launched initiatives for sharing not only data but entire pipelines, derivatives, artifacts, etc.
MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
As a demonstration of the importance of this new dataset, we present a comparative study of the effect of the inclusion of ratings on non-item KG entities in a variety of state-of-the-art recommendation models.
The Odyssey Approach for Optimizing Federated SPARQL Queries
Our experimental results show that Odyssey produces query execution plans that are better in terms of data transfer and execution time than state-of-the-art optimizers.
Databases
