Cargando…

Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature

Phylogeography research involving virus spread and tree reconstruction relies on accurate geographic locations of infected hosts. Insufficient level of geographic information in nucleotide sequence repositories such as GenBank motivates the use of natural language processing methods for extracting g...

Descripción completa

Detalles Bibliográficos
Autores principales:	Magge, Arjun, Weissenbacher, Davy, Sarker, Abeed, Scotch, Matthew, Gonzalez-Hernandez, Graciela
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	2019
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417823/ https://www.ncbi.nlm.nih.gov/pubmed/30864314

Ejemplares similares

Deep neural networks and distant supervision for geographic location mention extraction
por: Magge, Arjun, et al.
Publicado: (2018)

Extracting geographic locations from the literature for virus phylogeography using supervised and distant supervision methods
por: Weissenbacher, Davy, et al.
Publicado: (2017)

Deep neural networks ensemble for detecting medication mentions in tweets
por: Weissenbacher, Davy, et al.
Publicado: (2019)

SEED: Symptom Extraction from English Social Media Posts using Deep Learning and Transfer Learning
por: Magge, Arjun, et al.
Publicado: (2022)

Comment on: “Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts”
por: Magge, Arjun, et al.
Publicado: (2019)

GeoBoost2: a natural languageprocessing pipeline for GenBank metadata enrichment for virus phylogeography
por: Magge, Arjun, et al.
Publicado: (2020)

A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter
por: Klein, Ari Z., et al.
Publicado: (2020)

Extending A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter to England, UK
por: Golder, S, et al.
Publicado: (2020)

A chronological and geographical analysis of personal reports of COVID-19 on Twitter from the UK
por: Golder, Su, et al.
Publicado: (2022)

Towards scaling Twitter for digital epidemiology of birth defects
por: Klein, Ari Z., et al.
Publicado: (2019)

Incorporating sampling uncertainty in the geospatial assignment of taxa for virus phylogeography
por: Scotch, Matthew, et al.
Publicado: (2019)

Knowledge-driven geospatial location resolution for phylogeographic models of virus migration
por: Weissenbacher, Davy, et al.
Publicado: (2015)

DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter
por: Magge, Arjun, et al.
Publicado: (2021)

Named entity linking of geospatial and host metadata in GenBank for advancing biomedical research
por: Tahsin, Tasnia, et al.
Publicado: (2017)

Discovering Cohorts of Pregnant Women From Social Media for Safety Surveillance and Analysis
por: Sarker, Abeed, et al.
Publicado: (2017)

Text mining biomedical literature to identify extremely unbalanced data for digital epidemiology and systematic reviews: dataset and methods for a SARS-CoV-2 genomic epidemiology study
por: Weissenbacher, Davy, et al.
Publicado: (2023)

Patient-Related Metadata Reported in Sequencing Studies of SARS-CoV-2: Protocol for a Scoping Review and Bibliometric Analysis
por: O’Connor, Karen, et al.
Publicado: (2023)

Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set
por: Klein, Ari Z, et al.
Publicado: (2021)

LexExp: a system for automatically expanding concept lexicons for noisy biomedical texts
por: Sarker, Abeed
Publicado: (2020)

ZooPhy: A bioinformatics pipeline for virus phylogeography and surveillance
por: Scotch, Matthew, et al.
Publicado: (2019)

ReportAGE: Automatically extracting the exact age of Twitter users based on self-reports in tweets
por: Klein, Ari Z., et al.
Publicado: (2022)

Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter
por: Sarker, Abeed, et al.
Publicado: (2016)

A corpus for mining drug-related knowledge from Twitter chatter: Language models and their utilities
por: Sarker, Abeed, et al.
Publicado: (2016)

Active neural networks to detect mentions of changes to medication treatment in social media
por: Weissenbacher, Davy, et al.
Publicado: (2021)

Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter
por: Sarker, Abeed, et al.
Publicado: (2019)

Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts
por: Korkontzelos, Ioannis, et al.
Publicado: (2016)

Promoting Reproducible Research for Characterizing Nonmedical Use of Medications Through Data Annotation: Description of a Twitter Corpus and Guidelines
por: O'Connor, Karen, et al.
Publicado: (2020)

Natural Language Processing Methods for Enhancing Geographic Metadata for Phylogeography of Zoonotic Viruses
por: Tahsin, Tasnia, et al.
Publicado: (2014)

Advances in Text Mining and Visualization for Precision Medicine
por: Gonzalez-Hernandez, Graciela, et al.
Publicado: (2018)

Automatically Identifying Twitter Users for Interventions to Support Dementia Family Caregivers: Annotated Data Set and Benchmark Classification Models
por: Klein, Ari Z, et al.
Publicado: (2022)

An empirical evaluation of electronic annotation tools for Twitter data
por: Weissenbacher, Davy, et al.
Publicado: (2020)

Predicting geographic location from genetic variation with deep neural networks
por: Battey, CJ, et al.
Publicado: (2020)

Location, Location, Location: The Geographic Impact of Medical School on the Plastic Surgery Match
por: Glener, Adam D., et al.
Publicado: (2021)

Geographic location of CERN.
por: Jean-Luc Caron
Publicado: (1998)

Patient-Reported Reasons for Switching or Discontinuing Statin Therapy: A Mixed Methods Study Using Social Media
por: Golder, Su, et al.
Publicado: (2022)

BiOnt: Deep Learning Using Multiple Biomedical Ontologies for Relation Extraction
por: Sousa, Diana, et al.
Publicado: (2020)

Methods to Compare Adverse Events in Twitter to FAERS, Drug Information Databases, and Systematic Reviews: Proof of Concept with Adalimumab
por: Smith, Karen, et al.
Publicado: (2018)

Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
por: Nikfarjam, Azadeh, et al.
Publicado: (2015)

Pregnancy and health in the age of the Internet: A content analysis of online “birth club” forums
por: Wexler, Anna, et al.
Publicado: (2020)

Broad-coverage biomedical relation extraction with SemRep
por: Kilicoglu, Halil, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_8r67td1jha4p808bge2u59hoae