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Found 5 papers, 1 papers with code
Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)
However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.
MapperGPT: Large Language Models for Linking and Mapping Entities
Here we present MapperGPT, an approach that uses LLMs to review and refine mapping relationships as a post-processing step, in concert with existing high-recall methods that are based on lexical and structural heuristics.
An evaluation of GPT models for phenotype concept recognition
Objective: Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field.
KG-Hub -- Building and Exchanging Biological Knowledge Graphs
Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of knowledge graphs is lacking.
Analyzing historical diagnosis code data from NIH N3C and RECOVER Programs using deep learning to determine risk factors for Long Covid
Using our deep learning approach, we are able to predict if a patient is suffering from Long COVID from a temporally ordered list of diagnosis codes up to 45 days post the first COVID positive test or diagnosis for each patient, with an accuracy of 70. 48\%.
