Cargando…

Using electronic medical record data to establish and monitor the distribution of refractive errors(,)

OBJECTIVE: To establish the baseline distribution of refractive errors and associated factors amongst a population that attended primary care optometry clinics. DESIGN: Retrospective cross sectional cohort study of electronic medical records (EMR). METHODS: Electronic medical record data was extract...

Descripción completa

Detalles Bibliográficos
Autores principales:	Longwill, Seán, Moore, Michael, Flitcroft, Daniel Ian, Loughman, James
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2022
Materias:	Artificial Intelligence
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732486/ https://www.ncbi.nlm.nih.gov/pubmed/36220741 http://dx.doi.org/10.1016/j.optom.2022.09.001

Ejemplares similares

Leveraging Open Electronic Health Record Data and Environmental Exposures Data to Derive Insights Into Rare Pulmonary Disease
por: Fecho, Karamarie, et al.
Publicado: (2022)

Prediction of manifest refraction using machine learning ensemble models on wavefront aberrometry data
por: Hernández, Carlos S., et al.
Publicado: (2022)

Application of big-data for epidemiological studies of refractive error
por: Moore, Michael, et al.
Publicado: (2021)

Developing and testing a prediction model for periodontal disease using machine learning and big electronic dental record data
por: Patel, Jay S., et al.
Publicado: (2022)

The Refractive Error and Vision Impairment Estimation with Spectacle Data Study
por: Moore, Michael, et al.
Publicado: (2021)

Assessing longitudinal housing status using Electronic Health Record data: a comparison of natural language processing, structured data, and patient-reported history
por: Chapman, Alec B., et al.
Publicado: (2023)

Error driven synapse augmented neurogenesis
por: Perrett, Adam, et al.
Publicado: (2022)

Distribution-preserving data augmentation
por: Saran, Nurdan Ayse, et al.
Publicado: (2021)

Analysis of cause-effect inference by comparing regression errors
por: Blöbaum, Patrick, et al.
Publicado: (2019)

CowMesh: a data-mesh architecture to unify dairy industry data for prediction and monitoring
por: Pakrashi, Arjun, et al.
Publicado: (2023)

Record linkage of banks and municipalities through multiple criteria and neural networks
por: Maratea, Antonio, et al.
Publicado: (2020)

Monitoring Weeder Robots and Anticipating Their Functioning by Using Advanced Topological Data Analysis
por: Frahi , Tarek, et al.
Publicado: (2021)

“I don’t Think These Devices are Very Culturally Sensitive.”—Impact of Automated Speech Recognition Errors on African Americans
por: Mengesha, Zion, et al.
Publicado: (2021)

Distributional Measures of Semantic Abstraction
por: Schulte im Walde, Sabine, et al.
Publicado: (2022)

Intelligent lecture recording system based on coordination of face-detection and pedestrian dead reckoning
por: Wang, Hu, et al.
Publicado: (2022)

Imagining the city in lockdown: Place in the COVID-19 self-recordings of the Lothian Diary Project
por: Cowie, Claire, et al.
Publicado: (2022)

The analysis of the structural parameter influences on measurement errors in a binocular 3D reconstruction system: a portable 3D system
por: Sha, Ou, et al.
Publicado: (2023)

SFedChain: blockchain-based federated learning scheme for secure data sharing in distributed energy storage networks
por: Meng, Mingming, et al.
Publicado: (2022)

Utility of Crowdsourced User Experiments for Measuring the Central Tendency of User Performance: A Case of Error-Rate Model Evaluation in a Pointing Task
por: Yamanaka, Shota
Publicado: (2022)

Topic2features: a novel framework to classify noisy and sparse textual data using LDA topic distributions
por: Wahid, Junaid Abdul, et al.
Publicado: (2021)

Collective view: mapping Sargassum distribution along beaches
por: Arellano-Verdejo, Javier, et al.
Publicado: (2021)

Distributed search and fusion for wine label image retrieval
por: Li, Xiaoqing, et al.
Publicado: (2022)

Secure biometric authentication with de-duplication on distributed cloud storage
por: M, Vinoth Kumar, et al.
Publicado: (2021)

Morphology in a Parallel, Distributed, Interactive Architecture of Language Production
por: Kapatsinski, Vsevolod
Publicado: (2022)

On Distributed Cognition While Designing an AI System for Adapted Learning
por: Aarset, Magne V., et al.
Publicado: (2022)

Gamma and vega hedging using deep distributional reinforcement learning
por: Cao, Jay, et al.
Publicado: (2023)

Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics
por: Bruera, Andrea, et al.
Publicado: (2022)

Distributed cognition for collaboration between human drivers and self-driving cars
por: Plebe, Alice, et al.
Publicado: (2022)

Challenges of Developing Robust AI for Intrapartum Fetal Heart Rate Monitoring
por: O’Sullivan, M. E., et al.
Publicado: (2021)

Autonomous Tool for Monitoring Multi-Morbidity Health Conditions in UAE and India
por: Atalla, Shadi, et al.
Publicado: (2022)

Artificial intelligence-assisted air quality monitoring for smart city management
por: Neo, En Xin, et al.
Publicado: (2023)

Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future
por: Grinschgl, Sandra, et al.
Publicado: (2022)

Differences between remote and analog design thinking through the lens of distributed cognition
por: Wolferts, Daniel, et al.
Publicado: (2022)

A Machine Learning Approach to Monitor the Emergence of Late Intrauterine Growth Restriction
por: Pini, Nicolò, et al.
Publicado: (2021)

How to get best predictions for road monitoring using machine learning techniques
por: Ferjani, Imen, et al.
Publicado: (2022)

Monitoring the Progression of Clinically Suspected Microbial Keratitis Using Convolutional Neural Networks
por: Kuo, Ming-Tse, et al.
Publicado: (2023)

Medical Information Mart for Intensive Care: A Foundation for the Fusion of Artificial Intelligence and Real-World Data
por: Rogers, Paul, et al.
Publicado: (2021)

Pilot Study of Real-World Monitoring of the Heart Rate Variability in Amyotrophic Lateral Sclerosis
por: Brown, Alexander A., et al.
Publicado: (2022)

Toward fault tolerant modelling for SCADA based electricity distribution networks, machine learning approach
por: Masri, Aladdin, et al.
Publicado: (2021)

Estimating distribution shifts for predicting cross-subject generalization in electroencephalography-based mental workload assessment
por: Albuquerque, Isabela, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_0rhuv8hpp6kmusml2181bhmoba