Cargando…

Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis

Background As adoption of electronic health records continues to increase, there is an opportunity to incorporate clinical documentation as well as laboratory values and demographics into risk prediction modeling. Objective The authors develop a risk prediction model for chronic kidney disease (CKD)...

Descripción completa

Detalles Bibliográficos
Autores principales:	Perotte, Adler, Ranganath, Rajesh, Hirsch, Jamie S, Blei, David, Elhadad, Noémie
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2015
Materias:	Research and Applications
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482276/ https://www.ncbi.nlm.nih.gov/pubmed/25896647 http://dx.doi.org/10.1093/jamia/ocv024

Ejemplares similares

Parameterizing time in electronic health record studies
por: Hripcsak, George, et al.
Publicado: (2015)

Diagnosis code assignment: models and evaluation metrics
por: Perotte, Adler, et al.
Publicado: (2014)

Characterizing non-heroin opioid overdoses using electronic health records
por: Averitt, Amelia J, et al.
Publicado: (2019)

Development and validation of prediction models for mechanical ventilation, renal replacement therapy, and readmission in COVID-19 patients
por: Rodriguez, Victor Alfonso, et al.
Publicado: (2021)

Automated methods for the summarization of electronic health records
por: Pivovarov, Rimma, et al.
Publicado: (2015)

Cross-lingual Unified Medical Language System entity linking in online health communities
por: Bitton, Yonatan, et al.
Publicado: (2020)

A neuro-symbolic method for understanding free-text medical evidence
por: Kang, Tian, et al.
Publicado: (2021)

Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies
por: Cohen, Raphael, et al.
Publicado: (2013)

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms
por: Albers, D.J., et al.
Publicado: (2018)

A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history
por: Maurits, Marc P, et al.
Publicado: (2022)

A predictive model for next cycle start date that accounts for adherence in menstrual self-tracking
por: Li, Kathy, et al.
Publicado: (2021)

The electronic elephant in the room: Physicians and the electronic health record
por: Kroth, Philip J, et al.
Publicado: (2018)

HIV Risk Assessment using Longitudinal Electronic Health Records
por: Feller, Daniel, et al.
Publicado: (2017)

The influence of a Sprint optimization and training intervention on time spent in the electronic health record (EHR)
por: Sieja, Amber, et al.
Publicado: (2021)

Multi-perspective predictive modeling for acute kidney injury in general hospital populations using electronic medical records
por: He, Jianqin, et al.
Publicado: (2018)

Natural language processing and machine learning of electronic health records for prediction of first-time suicide attempts
por: Tsui, Fuchiang R, et al.
Publicado: (2021)

Dynamical Phenotyping: Using Temporal Analysis of Clinically Collected Physiologic Data to Stratify Populations
por: Albers, D. J., et al.
Publicado: (2014)

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record
por: Corbin, Conor K, et al.
Publicado: (2023)

Redundancy-Aware Topic Modeling for Patient Record Notes
por: Cohen, Raphael, et al.
Publicado: (2014)

Electronic health records improve clinical note quality
por: Burke, Harry B, et al.
Publicado: (2015)

Electronic health records and support for primary care teamwork
por: O’Malley, Ann S., et al.
Publicado: (2015)

Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study
por: Sottile, Peter D, et al.
Publicado: (2021)

Evaluating the state of the art in disorder recognition and normalization of the clinical narrative
por: Pradhan, Sameer, et al.
Publicado: (2015)

An analysis of electronic health record-related patient safety concerns
por: Meeks, Derek W, et al.
Publicado: (2014)

Correlating electronic health record concepts with healthcare process events
por: Hripcsak, George, et al.
Publicado: (2013)

Efficiency and safety of speech recognition for documentation in the electronic health record
por: Hodgson, Tobias, et al.
Publicado: (2017)

A simple electronic medical record system designed for research
por: King, Andrew J, et al.
Publicado: (2021)

HARVEST, a longitudinal patient record summarizer
por: Hirsch, Jamie S, et al.
Publicado: (2015)

Validity of electronic health record-derived quality measurement for performance monitoring
por: Parsons, Amanda, et al.
Publicado: (2012)

Automated extraction of clinical traits of multiple sclerosis in electronic medical records
por: Davis, Mary F, et al.
Publicado: (2013)

Desiderata for computable representations of electronic health records-driven phenotype algorithms
por: Mo, Huan, et al.
Publicado: (2015)

Synergistic drug combinations from electronic health records and gene expression
por: Low, Yen S, et al.
Publicado: (2017)

Research use of electronic health records: patients’ perspectives on contact by researchers
por: Brelsford, Kathleen M, et al.
Publicado: (2018)

Provider perspectives on the integration of patient-reported outcomes in an electronic health record
por: Zhang, Renwen, et al.
Publicado: (2019)

Characterizing outpatient problem list completeness and duplications in the electronic health record
por: Wang, Edward Chia-Heng, et al.
Publicado: (2020)

Test collections for electronic health record-based clinical information retrieval
por: Wang, Yanshan, et al.
Publicado: (2019)

Characterizing employment of colorectal cancer survivors using electronic health records
por: Varga, Alexandra, et al.
Publicado: (2021)

The SMART Platform: early experience enabling substitutable applications for electronic health records
por: Mandl, Kenneth D, et al.
Publicado: (2012)

Physician champions’ perspectives and practices on electronic health records implementation: challenges and strategies
por: Gui, Xinning, et al.
Publicado: (2020)

UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER
por: Denaxas, Spiros, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_98af8bob6c1u9qtitgvs25qmd8