Page: 1 2 3 4 5 6 7... 1.020
47 |
NLPropTest: Parsing English to Property-Based Tests with Categorial Grammars ...
|
|
|
|
BASE
|
|
Show details
|
|
48 |
NLPropTest: Parsing English to Property-Based Tests with Categorial Grammars ...
|
|
|
|
BASE
|
|
Show details
|
|
49 |
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse ...
|
|
|
|
BASE
|
|
Show details
|
|
50 |
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
|
|
|
|
BASE
|
|
Show details
|
|
51 |
Pemanfaatan Bank-data Digital Dwibahasa dalam Kajian Terjemahan: Studi kasus padanan bahasa Indonesia untuk verba sinonim bahasa Inggris ROB & STEAL ...
|
|
|
|
BASE
|
|
Show details
|
|
52 |
Pemanfaatan Bank-data Digital Dwibahasa dalam Kajian Terjemahan: Studi kasus padanan bahasa Indonesia untuk verba sinonim bahasa Inggris ROB & STEAL ...
|
|
|
|
BASE
|
|
Show details
|
|
53 |
Chances and Challenges for Quantitative Approaches in Chinese Historical Phonology ...
|
|
|
|
BASE
|
|
Show details
|
|
54 |
Computational Approaches to Historical Language Comparison ...
|
|
|
|
BASE
|
|
Show details
|
|
55 |
The glyph project: The distinctiveness of written characters — online crowdsourcing for a typology of letter shapes ...
|
|
|
|
BASE
|
|
Show details
|
|
56 |
Backchannel Behavior Influences the Perceived Personality of Human and Artificial Communication Partners
|
|
|
|
BASE
|
|
Show details
|
|
57 |
Found speech and humans in the loop : Ways to gain insight into large quantities of speech
|
|
|
|
BASE
|
|
Show details
|
|
58 |
Is a Wizard-of-Oz Required for Robot-Led Conversation Practice in a Second Language?
|
|
Águas Lopes, José David; Cumbal, Ronald; Engwall, Olov. - : KTH, Tal-kommunikation, 2022. : KTH, Tal, musik och hörsel, TMH, 2022. : Springer Nature, 2022
|
|
BASE
|
|
Show details
|
|
59 |
Using Machine Learning for Pharmacovigilance: A Systematic Review
|
|
|
|
In: Pharmaceutics; Volume 14; Issue 2; Pages: 266 (2022)
|
|
Abstract:
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 time-consuming. The application of natural language processing (NLP) to analyze user-generated content is hypothesized as an effective supplemental source of evidence. In this systematic review, a broad and multi-disciplinary literature search was conducted involving four databases. A total of 5318 publications were initially found. Studies were considered relevant if they reported on the application of NLP to understand user-generated text for pharmacovigilance. A total of 16 relevant publications were included in this systematic review. All studies were evaluated to have medium reliability and validity. For all types of drugs, 14 publications reported positive findings with respect to the identification of adverse drug reactions, providing consistent evidence that natural language processing can be used effectively and accurately on user-generated textual content that was published to the Internet to identify adverse drug reactions for the purpose of pharmacovigilance. The evidence presented in this review suggest that the analysis of textual data has the potential to complement the traditional system of pharmacovigilance.
|
|
Keyword:
ADRs; adverse drug reactions; computational linguistics; machine learning; pharmacovigilance; public health; user-generated content
|
|
URL: https://doi.org/10.3390/pharmaceutics14020266
|
|
BASE
|
|
Hide details
|
|
60 |
Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study
|
|
|
|
In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022)
|
|
BASE
|
|
Show details
|
|
Page: 1 2 3 4 5 6 7... 1.020
|
|