Learning from disagreement: A survey
Abstract Many tasks in Natural Language Processing (NLP) and Computer Vision (CV) offer
evidence that humans disagree, from objective tasks such as part-of-speech tagging to more …
evidence that humans disagree, from objective tasks such as part-of-speech tagging to more …
[PDF][PDF] Classifying relations via long short term memory networks along shortest dependency paths
Relation classification is an important research arena in the field of natural language
processing (NLP). In this paper, we present SDP-LSTM, a novel neural network to classify …
processing (NLP). In this paper, we present SDP-LSTM, a novel neural network to classify …
Learning for biomedical information extraction: Methodological review of recent advances
F Liu, J Chen, A Jagannatha, H Yu - arXiv preprint arXiv:1606.07993, 2016 - arxiv.org
Biomedical information extraction (BioIE) is important to many applications, including clinical
decision support, integrative biology, and pharmacovigilance, and therefore it has been an …
decision support, integrative biology, and pharmacovigilance, and therefore it has been an …
Toward a learning health-care system–knowledge delivery at the point of care empowered by big data and NLP
VC Kaggal, RK Elayavilli, S Mehrabi… - Biomedical …, 2016 - journals.sagepub.com
The concept of optimizing health care by understanding and generating knowledge from
previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and …
previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and …
[HTML][HTML] Medical knowledge graph to enhance fraud, waste, and abuse detection on claim data: Model development and performance evaluation
H Sun, J Xiao, W Zhu, Y He, S Zhang… - JMIR Medical …, 2020 - medinform.jmir.org
Background: Fraud, Waste, and Abuse (FWA) detection is a significant yet challenging
problem in the health insurance industry. An essential step in FWA detection is to check …
problem in the health insurance industry. An essential step in FWA detection is to check …
Crowdsourcing ground truth for medical relation extraction
Cognitive computing systems require human labeled data for evaluation and often for
training. The standard practice used in gathering this data minimizes disagreement between …
training. The standard practice used in gathering this data minimizes disagreement between …
Classifying relations via long short term memory networks along shortest dependency path
Relation classification is an important research arena in the field of natural language
processing (NLP). In this paper, we present SDP-LSTM, a novel neural network to classify …
processing (NLP). In this paper, we present SDP-LSTM, a novel neural network to classify …
Unsupervised entity and relation extraction from clinical records in Italian
This paper proposes and discusses the use of text mining techniques for the extraction of
information from clinical records written in Italian. However, as it is very difficult and …
information from clinical records written in Italian. However, as it is very difficult and …
A general approach for improving deep learning-based medical relation extraction using a pre-trained model and fine-tuning
T Chen, M Wu, H Li - Database, 2019 - academic.oup.com
The automatic extraction of meaningful relations from biomedical literature or clinical records
is crucial in various biomedical applications. Most of the current deep learning approaches …
is crucial in various biomedical applications. Most of the current deep learning approaches …
[HTML][HTML] KeMRE: Knowledge-enhanced medical relation extraction for Chinese medicine instructions
Medicine instructions usually contain rich medical relations, and extracting them is very
helpful for many downstream tasks such as medicine knowledge graph construction and …
helpful for many downstream tasks such as medicine knowledge graph construction and …