Detalhe da pesquisa
1.
The Tool for Automatic Measurement of Morphological Information (TAMMI).
Behav Res Methods
; 2023 Dec 29.
Artigo
Inglês
| MEDLINE | ID: mdl-38158554
2.
A large-scaled corpus for assessing text readability.
Behav Res Methods
; 55(2): 491-507, 2023 02.
Artigo
Inglês
| MEDLINE | ID: mdl-35297016
3.
Age of Exposure 2.0: Estimating word complexity using iterative models of word embeddings.
Behav Res Methods
; 54(6): 3015-3042, 2022 12.
Artigo
Inglês
| MEDLINE | ID: mdl-35167112
4.
Challenges and solutions to employing natural language processing and machine learning to measure patients' health literacy and physician writing complexity: The ECLIPPSE study.
J Biomed Inform
; 113: 103658, 2021 01.
Artigo
Inglês
| MEDLINE | ID: mdl-33316421
5.
Developing and Testing Automatic Models of Patient Communicative Health Literacy Using Linguistic Features: Findings from the ECLIPPSE study.
Health Commun
; 36(8): 1018-1028, 2021 07.
Artigo
Inglês
| MEDLINE | ID: mdl-32114833
6.
Secure Messaging with Physicians by Proxies for Patients with Diabetes: Findings from the ECLIPPSE Study.
J Gen Intern Med
; 34(11): 2490-2496, 2019 11.
Artigo
Inglês
| MEDLINE | ID: mdl-31428986
7.
The Tool for the Automatic Analysis of Cohesion 2.0: Integrating semantic similarity and text overlap.
Behav Res Methods
; 51(1): 14-27, 2019 02.
Artigo
Inglês
| MEDLINE | ID: mdl-30298264
8.
The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0.
Behav Res Methods
; 50(3): 1030-1046, 2018 06.
Artigo
Inglês
| MEDLINE | ID: mdl-28699123
9.
Sentiment Analysis and Social Cognition Engine (SEANCE): An automatic tool for sentiment, social cognition, and social-order analysis.
Behav Res Methods
; 49(3): 803-821, 2017 06.
Artigo
Inglês
| MEDLINE | ID: mdl-27193159
10.
The tool for the automatic analysis of text cohesion (TAACO): Automatic assessment of local, global, and text cohesion.
Behav Res Methods
; 48(4): 1227-1237, 2016 12.
Artigo
Inglês
| MEDLINE | ID: mdl-26416138
11.
Natural language processing in an intelligent writing strategy tutoring system.
Behav Res Methods
; 45(2): 499-515, 2013 Jun.
Artigo
Inglês
| MEDLINE | ID: mdl-23055164
12.
Lexical and phraseological differences between second language written and spoken opinion responses.
Front Psychol
; 14: 1068685, 2023.
Artigo
Inglês
| MEDLINE | ID: mdl-36939413
13.
Do Struggling Adult Readers Monitor Their Reading? Understanding the Role of Online and Offline Comprehension Monitoring Processes During Reading.
J Learn Disabil
; 56(1): 25-42, 2023.
Artigo
Inglês
| MEDLINE | ID: mdl-35321590
14.
The persuasive essays for rating, selecting, and understanding argumentative and discourse elements (PERSUADE) corpus 1.0.
Assess Writ
; 54: None, 2022 Oct.
Artigo
Inglês
| MEDLINE | ID: mdl-36570517
15.
Validity of a Computational Linguistics-Derived Automated Health Literacy Measure Across Race/Ethnicity: Findings from The ECLIPPSE Project.
J Health Care Poor Underserved
; 32(2 Suppl): 347-365, 2021 05.
Artigo
Inglês
| MEDLINE | ID: mdl-36101652
16.
Precision communication: Physicians' linguistic adaptation to patients' health literacy.
Sci Adv
; 7(51): eabj2836, 2021 Dec 17.
Artigo
Inglês
| MEDLINE | ID: mdl-34919437
17.
Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study.
Health Serv Res
; 56(1): 132-144, 2021 02.
Artigo
Inglês
| MEDLINE | ID: mdl-32966630
18.
Descriptive examination of secure messaging in a longitudinal cohort of diabetes patients in the ECLIPPSE study.
J Am Med Inform Assoc
; 28(6): 1252-1258, 2021 06 12.
Artigo
Inglês
| MEDLINE | ID: mdl-33236117
19.
Predicting the readability of physicians' secure messages to improve health communication using novel linguistic features: Findings from the ECLIPPSE study.
J Commun Healthc
; 13(4): 1-13, 2020.
Artigo
Inglês
| MEDLINE | ID: mdl-34306181
20.
Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study.
PLoS One
; 14(2): e0212488, 2019.
Artigo
Inglês
| MEDLINE | ID: mdl-30794616