[HTML][HTML] Integrating domain knowledge for biomedical text analysis into deep learning: A survey
The past decade has witnessed an explosion of textual information in the biomedical field.
Biomedical texts provide a basis for healthcare delivery, knowledge discovery, and decision …
Biomedical texts provide a basis for healthcare delivery, knowledge discovery, and decision …
Physics of language models: Part 3.1, knowledge storage and extraction
Large language models can store extensive world knowledge, often extractable through
question-answering (eg," What is Abraham Lincoln's birthday?"). However, it's unclear …
question-answering (eg," What is Abraham Lincoln's birthday?"). However, it's unclear …
Combating the COVID-19 infodemic using Prompt-Based curriculum learning
The COVID-19 pandemic has been accompanied by a proliferation of online misinformation
and disinformation about the virus. Combating this 'infodemic'has been identified as one of …
and disinformation about the virus. Combating this 'infodemic'has been identified as one of …
Developing a general-purpose clinical language inference model from a large corpus of clinical notes
Several biomedical language models have already been developed for clinical language
inference. However, these models typically utilize general vocabularies and are trained on …
inference. However, these models typically utilize general vocabularies and are trained on …
NCUEE-NLP at SemEval-2023 Task 7: Ensemble Biomedical LinkBERT Transformers in Multi-evidence Natural Language Inference for Clinical Trial Data
CY Chen, KY Tien, YH Cheng… - Proceedings of the 17th …, 2023 - aclanthology.org
This study describes the model design of the NCUEE-NLP system for the SemEval-2023
NLI4CT task that focuses on multi-evidence natural language inference for clinical trial data …
NLI4CT task that focuses on multi-evidence natural language inference for clinical trial data …
[HTML][HTML] Ensemble learning with soft-prompted pretrained language models for fact checking
S Huang, Y Wang, EYC Wong, L Yu - Natural Language Processing …, 2024 - Elsevier
The infectious diseases, such as COVID-19 pandemic, has led to a surge of information on
the internet, including misinformation, necessitating fact-checking tools. However, fact …
the internet, including misinformation, necessitating fact-checking tools. However, fact …
H-COAL: Human Correction of AI-Generated Labels for Biomedical Named Entity Recognition
X Duan, JP Lalor - arXiv preprint arXiv:2311.11981, 2023 - arxiv.org
With the rapid advancement of machine learning models for NLP tasks, collecting high-
fidelity labels from AI models is a realistic possibility. Firms now make AI available to …
fidelity labels from AI models is a realistic possibility. Firms now make AI available to …
Domain adaptive multi-task transformer for low-resource machine reading comprehension
In recent years, low-resource Machine Reading Comprehension (MRC) attracts increasing
attention. Due to the difficulty in data collecting, current low-resource MRC approaches often …
attention. Due to the difficulty in data collecting, current low-resource MRC approaches often …
Automated Clinical Data Extraction with Knowledge Conditioned LLMs
The extraction of lung lesion information from clinical and medical imaging reports is crucial
for research on and clinical care of lung-related diseases. Large language models (LLMs) …
for research on and clinical care of lung-related diseases. Large language models (LLMs) …
A Study on the Impacts of Slot Types and Training Data on Joint Natural Language Understanding in a Spanish Medication Management Assistant Scenario
This study evaluates the impacts of slot tagging and training data length on joint natural
language understanding (NLU) models for medication management scenarios using …
language understanding (NLU) models for medication management scenarios using …