[HTML][HTML] Capturing the patient's perspective: a review of advances in natural language processing of health-related text
G Gonzalez-Hernandez, A Sarker… - Yearbook of medical …, 2017 - thieme-connect.com
Background: Natural Language Processing (NLP) methods are increasingly being utilized to
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
Using machine learning for pharmacovigilance: a systematic review
Pharmacovigilance is a science that involves the ongoing monitoring of adverse drug
reactions to existing medicines. Traditional approaches in this field can be expensive and …
reactions to existing medicines. Traditional approaches in this field can be expensive and …
Adverse drug event detection in tweets with semi-supervised convolutional neural networks
Current Adverse Drug Events (ADE) surveillance systems are often associated with a
sizable time lag before such events are published. Online social media such as Twitter could …
sizable time lag before such events are published. Online social media such as Twitter could …
[HTML][HTML] Named entity recognition from Chinese adverse drug event reports with lexical feature based BiLSTM-CRF and tri-training
Y Chen, C Zhou, T Li, H Wu, X Zhao, K Ye… - Journal of biomedical …, 2019 - Elsevier
Abstract Background The Adverse Drug Event Reports (ADERs) from the spontaneous
reporting system are important data sources for studying Adverse Drug Reactions (ADRs) as …
reporting system are important data sources for studying Adverse Drug Reactions (ADRs) as …
Twitpersonality: Computing personality traits from tweets using word embeddings and supervised learning
We are what we do, like, and say. Numerous research efforts have been pushed towards the
automatic assessment of personality dimensions relying on a set of information gathered …
automatic assessment of personality dimensions relying on a set of information gathered …
Pharmacovigilance with Transformers: A Framework to Detect Adverse Drug Reactions Using BERT Fine‐Tuned with FARM
Adverse drug reactions (ADRs) are the undesirable effects associated with the use of a drug
due to some pharmacological action of the drug. During the last few years, social media has …
due to some pharmacological action of the drug. During the last few years, social media has …
Adverse drug event and medication extraction in electronic health records via a cascading architecture with different sequence labeling models and word embeddings
Objective An adverse drug event (ADE) refers to an injury resulting from medical intervention
related to a drug including harm caused by drugs or from the usage of drugs. Extracting …
related to a drug including harm caused by drugs or from the usage of drugs. Extracting …
[PDF][PDF] Feature engineering (FE) tools and techniques for better classification performance
T Rawat, V Khemchandani - International Journal of …, 2017 - datascienceassn.org
Feature engineering has been the focus of interest for some time and it is still limited or
under studied. Therefore, more determined attempts are required to help forward feature …
under studied. Therefore, more determined attempts are required to help forward feature …
Classifying adverse drug reactions from imbalanced twitter data
Background Nowadays, social media are often being used by general public to create and
share public messages related to their health. With the global increase in social media …
share public messages related to their health. With the global increase in social media …
Using a recurrent neural network model for classification of tweets conveyed influenza-related information
Traditional disease surveillance systems depend on outpatient reporting and virological test
results released by hospitals. These data have valid and accurate information about …
results released by hospitals. These data have valid and accurate information about …