Knowledge graphs in psychiatric research: Potential applications and future perspectives
S Freidel, E Schwarz - Acta Psychiatrica Scandinavica, 2024 - Wiley Online Library
Abstract Background Knowledge graphs (KGs) remain an underutilized tool in the field of
psychiatric research. In the broader biomedical field KGs are already a significant tool …
psychiatric research. In the broader biomedical field KGs are already a significant tool …
CASSI: Contextual and Semantic Structure-based Interpolation Augmentation for Low-Resource NER
While text augmentation methods have been successful in improving performance in the low-
resource setting, they suffer from annotation corruption for a token-level task like NER …
resource setting, they suffer from annotation corruption for a token-level task like NER …
Few shot clinical entity recognition in three languages: Masked language models outperform LLM prompting
BERT for complex systematic review screening to support the future of medical research
This work presents a Natural Language Processing approach to screen complex datasets of
medical articles to provide timely and efficient response to pressing issues in medicine. The …
medical articles to provide timely and efficient response to pressing issues in medicine. The …
A compressed large language model embedding dataset of ICD 10 CM descriptions
MJ Kane, C King, D Esserman, NK Latham… - BMC …, 2023 - Springer
This paper presents novel datasets providing numerical representations of ICD-10-CM
codes by generating description embeddings using a large language model followed by a …
codes by generating description embeddings using a large language model followed by a …
BERT for Complex Systematic Review Screening to Support the Future of Medical Research
I Domocos, M Dulloo, N Patel, O Drayson… - … in Medicine: 21st …, 2023 - books.google.com
This work presents a Natural Language Processing approach to screen complex datasets of
medical articles to provide timely and efficient response to pressing issues in medicine. The …
medical articles to provide timely and efficient response to pressing issues in medicine. The …
Unsupervised extraction, classification and visualization of clinical note segments using the MIMIC-III dataset
P Zelina, J Halámková… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
This paper presents a text-mining approach to extracting and organizing segments from
unstructured clinical notes in an unsupervised way. Our work is motivated by the real …
unstructured clinical notes in an unsupervised way. Our work is motivated by the real …
[PDF][PDF] Using Foundation Models to Prescribe Patients Proper Antibiotics
SA Lee, H Halperin, Y Halperin, T Brokowski… - 2025 - openreview.net
The rise of antibiotic-resistant bacteria presents a significant global health threat by reducing
the effectiveness of essential treatments. This study evaluates the potential of clinical …
the effectiveness of essential treatments. This study evaluates the potential of clinical …
Deep learning-based text augmentation for named entity recognition
T Surana - 2023 - dr.ntu.edu.sg
This thesis is focused on the development of an effective text augmentation method for
Named Entity Recognition (NER) in the low-resource setting. NER, an important sequence …
Named Entity Recognition (NER) in the low-resource setting. NER, an important sequence …