Cargando…

2063. Using Twitter Data and Machine Learning to Identify Outpatient Antibiotic Misuse: A Proof-of-Concept Study

BACKGROUND: Outpatient antibiotic misuse is common, yet it is difficult to identify and prevent. Novel methods are needed to better identify unnecessary antibiotic use in the outpatient setting. METHODS: The Twitter developer platform was accessed to identify Tweets describing outpatient antibiotic...

Descripción completa

Detalles Bibliográficos
Autor principal:	Sullivan, Timothy
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2019
Materias:	Abstracts
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6809283/ http://dx.doi.org/10.1093/ofid/ofz360.1743

Ejemplares similares

2063. Implementation of a Rapid HIV Screening Program in the Emergency Department
por: Geringer, Matthew, et al.
Publicado: (2022)

2063. Extracellular Release of β-Lactamase Is Responsible for the Cefazolin Inoculum Effect (CzIE) in Methicillin-Susceptible Staphylococcus aureus
por: Carvajal, Lina P, et al.
Publicado: (2018)

2063. Elucidating the Gram-Positive Selective Spectrum Activity of Ibezapolstat; Secondary Analysis from the phase 2a trial
por: Lancaster, Chris, et al.
Publicado: (2023)

Identifying schizophrenia stigma on Twitter: a proof of principle model using service user supervised machine learning
por: Jilka, Sagar, et al.
Publicado: (2022)

Machine Learning to Analyze Single-Case Data: A Proof of Concept
por: Lanovaz, Marc J., et al.
Publicado: (2020)

Using Twitter Data for Cohort Studies of Drug Safety in Pregnancy: Proof-of-concept With β-Blockers
por: Klein, Ari Z, et al.
Publicado: (2022)

Machine learning models predict the mTOR signal pathway-related signature in the gastric cancer involving 2063 samples of 7 centers
por: Zhang, Hao, et al.
Publicado: (2023)

2016. Antibiotic Misuse of Rural Residents and Pilot Project of Antibiotic Take-Back Program
por: Wang, Weiyi, et al.
Publicado: (2019)

Diagnosing Hemophagocytic Lymphohistiocytosis with Machine Learning: A Proof of Concept
por: El Jammal, Thomas, et al.
Publicado: (2022)

GJB2 mutation spectrum in 2063 Chinese patients with nonsyndromic hearing impairment
por: Dai, Pu, et al.
Publicado: (2009)

A proof of concept study for machine learning application to stenosis detection
por: Jones, Gareth, et al.
Publicado: (2021)

Predicting benzodiazepine prescriptions: A proof-of-concept machine learning approach
por: Kinney, Kerry L., et al.
Publicado: (2023)

Toward Using Twitter Data to Monitor COVID-19 Vaccine Safety in Pregnancy: Proof-of-Concept Study of Cohort Identification
por: Klein, Ari Z, et al.
Publicado: (2022)

Food allergy and anaphylaxis – 2063. Identification of foods causing hypersensitivity/ allergy among school children in two sub-urban schools in Colombo District, Sri Lanka
por: Wimalasiri, Y Sarangee G, et al.
Publicado: (2013)

Implicit data crimes: Machine learning bias arising from misuse of public data
por: Shimron, Efrat, et al.
Publicado: (2022)

Shortening the Current Opioid Misuse Measure via computer-based testing: a retrospective proof-of-concept study
por: Finkelman, Matthew D, et al.
Publicado: (2013)

Machine learning is the key to diagnose COVID-19: a proof-of-concept study
por: Gangloff, Cedric, et al.
Publicado: (2021)

A proof-of-concept study on mortality prediction with machine learning algorithms using burn intensive care data
por: Fransén, Jian, et al.
Publicado: (2022)

Public Discussion of Anthrax on Twitter: Using Machine Learning to Identify Relevant Topics and Events
por: Miller, Michele, et al.
Publicado: (2021)

A machine-learning algorithm to identify hepatitis C in health insurance claims data
por: Khan, Mohammed A., et al.
Publicado: (2019)

The role of the universally conserved A2450–C2063 base pair in the ribosomal peptidyl transferase center
por: Chirkova, Anna, et al.
Publicado: (2010)

PB2063: CHARACTERISTICS AND THERAPEUTIC RESULTS OF PATIENTS WITH REFRACTORY/RELAPSED HODGKIN LYMPHOMA IN A TUNISIAN CENTER
por: Kammoun, F., et al.
Publicado: (2022)

Machine learning methods to predict child posttraumatic stress: a proof of concept study
por: Saxe, Glenn N., et al.
Publicado: (2017)

A proof of concept for machine learning-based virtual knapping using neural networks
por: Orellana Figueroa, Jordy Didier, et al.
Publicado: (2021)

Machine Learning Decision Support for Detecting Lipohypertrophy With Bedside Ultrasound: Proof-of-Concept Study
por: Bandari, Ela, et al.
Publicado: (2022)

Machine learning used for simulation of MitraClip intervention: A proof-of-concept study
por: Dabiri, Yaghoub, et al.
Publicado: (2023)

Identifying High-Risk Areas for Dengue Infection Using Mobility Patterns on Twitter
por: Souza, Roberto C., et al.
Publicado: (2019)

Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients
por: Sharma, Brihat, 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)

Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality
por: Braithwaite, Scott R, et al.
Publicado: (2016)

Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza
por: Allen, Chris, et al.
Publicado: (2016)

Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study
por: Visweswaran, Shyam, et al.
Publicado: (2020)

The landscape of schizophrenia on twitter
por: Rodrigues, T., et al.
Publicado: (2021)

Trauma research at the scene of injury – proof of concept through collaboration
por: Clarkson, Aisling, et al.
Publicado: (2015)

Prevalence of Misuse of Topical Corticosteroid among Dermatology Outpatients
por: Shrestha, Shristi, et al.
Publicado: (2020)

1020. A Novel Quality Control Solution for Gram Stain Through Integration of Deep Learning Vision Technology: A Proof-of-Concept
por: Hata, Jane, et al.
Publicado: (2023)

Two Cases of Mycoplasma pneumoniae Pneumonia with A2063G Mutation in the 23S rRNA Gene in Siblings
por: Hong, Joo Hee, et al.
Publicado: (2013)

Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept
por: Tran, Nam K., et al.
Publicado: (2020)

Author Correction: Machine learning is the key to diagnose COVID-19: a proof-of-concept study
por: Gangloff, Cedric, et al.
Publicado: (2021)

Machine learning to predict in‐hospital mortality among patients with severe obesity: Proof of concept study
por: Soffer, Shelly, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_20l2cl7g8mkant1r0v6u0gef4u