Detalhe da pesquisa
1.
Can accurate demographic information about people who use prescription medications nonmedically be derived from Twitter?
Proc Natl Acad Sci U S A
; 120(8): e2207391120, 2023 02 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-36787355
2.
A large language model-based generative natural language processing framework fine-tuned on clinical notes accurately extracts headache frequency from electronic health records.
Headache
; 64(4): 400-409, 2024 Apr.
Artigo
em Inglês
| MEDLINE | ID: mdl-38525734
3.
Few-shot learning for medical text: A review of advances, trends, and opportunities.
J Biomed Inform
; 144: 104458, 2023 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-37488023
4.
Automatic Detection of Twitter Users Who Express Chronic Stress Experiences via Supervised Machine Learning and Natural Language Processing.
Comput Inform Nurs
; 41(9): 717-724, 2023 Sep 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-36445331
5.
LexExp: a system for automatically expanding concept lexicons for noisy biomedical texts.
Bioinformatics
; 37(16): 2499-2501, 2021 08 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-33244602
6.
Evidence of the emergence of illicit benzodiazepines from online drug forums.
Eur J Public Health
; 32(6): 939-941, 2022 11 29.
Artigo
em Inglês
| MEDLINE | ID: mdl-36342855
7.
Signals of increasing co-use of stimulants and opioids from online drug forum data.
Harm Reduct J
; 19(1): 51, 2022 05 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-35614501
8.
Developing an Automatic System for Classifying Chatter About Health Services on Twitter: Case Study for Medicaid.
J Med Internet Res
; 23(5): e26616, 2021 05 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-33938807
9.
Text classification models for the automatic detection of nonmedical prescription medication use from social media.
BMC Med Inform Decis Mak
; 21(1): 27, 2021 01 26.
Artigo
em Inglês
| MEDLINE | ID: mdl-33499852
10.
Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach.
J Med Internet Res
; 22(8): e18401, 2020 08 17.
Artigo
em Inglês
| MEDLINE | ID: mdl-32804085
11.
Promoting Reproducible Research for Characterizing Nonmedical Use of Medications Through Data Annotation: Description of a Twitter Corpus and Guidelines.
J Med Internet Res
; 22(2): e15861, 2020 02 26.
Artigo
em Inglês
| MEDLINE | ID: mdl-32130117
12.
Deep neural networks and distant supervision for geographic location mention extraction.
Bioinformatics
; 34(13): i565-i573, 2018 07 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-29950020
13.
An interpretable natural language processing system for written medical examination assessment.
J Biomed Inform
; 98: 103268, 2019 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-31421211
14.
An unsupervised and customizable misspelling generator for mining noisy health-related text sources.
J Biomed Inform
; 88: 98-107, 2018 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-30445220
15.
Social media mining for birth defects research: A rule-based, bootstrapping approach to collecting data for rare health-related events on Twitter.
J Biomed Inform
; 87: 68-78, 2018 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-30292855
16.
Discovering Cohorts of Pregnant Women From Social Media for Safety Surveillance and Analysis.
J Med Internet Res
; 19(10): e361, 2017 10 30.
Artigo
em Inglês
| MEDLINE | ID: mdl-29084707
17.
Query-oriented evidence extraction to support evidence-based medicine practice.
J Biomed Inform
; 59: 169-84, 2016 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-26631762
18.
Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts.
J Biomed Inform
; 62: 148-58, 2016 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-27363901
19.
Portable automatic text classification for adverse drug reaction detection via multi-corpus training.
J Biomed Inform
; 53: 196-207, 2015 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-25451103
20.
Utilizing social media data for pharmacovigilance: A review.
J Biomed Inform
; 54: 202-12, 2015 Apr.
Artigo
em Inglês
| MEDLINE | ID: mdl-25720841