Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.
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Predicting mortality over different time horizons: which data elements are needed?An external validation of models to predict the onset of chronic kidney disease using population-based electronic health records from Salford, UK.Ethics and Epistemology in Big Data Research.Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records.A comparison of risk prediction methods using repeated observations: an application to electronic health records for hemodialysis.Use of Population Pharmacokinetics and Electronic Health Records to Assess Piperacillin-Tazobactam Safety in Infants.Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges.Risk Prediction With Electronic Health Records: The Importance of Model Validation and Clinical ContextImplementing Cardiovascular Risk Prediction in Clinical Practice: The Future Is Now.An electronic health record based model predicts statin adherence, LDL cholesterol, and cardiovascular disease in the United States Military Health System.Validation of an algorithm that determines stroke diagnostic code accuracy in a Japanese hospital-based cancer registry using electronic medical records.Clinical Information Extraction Applications: A Literature Review.Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning.Cognitive and Interpersonal Vulnerabilities to Adolescent Depression: Classification of Risk Profiles for a Personalized Prevention Approach.Machine learning and medicine: book review and commentary.Performing an Informatics Consult: Methods and Challenges.Designing risk prediction models for ambulatory no-shows across different specialties and clinics.Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay.Landmark Models for Optimizing the Use of Repeated Measurements of Risk Factors in Electronic Health Records to Predict Future Disease Risk.Feasibility of real-time capture of routine clinical data in the electronic health record: a hospital-based, observational service-evaluation study.Using big data to improve cardiovascular care and outcomes in China: a protocol for the CHinese Electronic health Records Research in Yinzhou (CHERRY) Study.Accurate and interpretable intensive care risk adjustment for fused clinical data with generalized additive models.Quantifying predictive capability of electronic health records for the most harmful breast cancer.Illustrating Informed Presence Bias in Electronic Health Records Data: How Patient Interactions with a Health System Can Impact Inference.Predictive Modeling of the Progression of Alzheimer's Disease with Recurrent Neural Networks.Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery diseaseDesign and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare dataNumeracy and Understanding of Quantitative Aspects of Predictive Models: A Pilot StudyValidating a Machine Learning Algorithm to Predict 30-Day Re-Admissions in Patients With Heart Failure: Protocol for a Prospective Cohort Study (Preprint)Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variablesA Survival Metadata Analysis Responsive Tool (SMART) for web-based analysis of patient survival and risk
P2860
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P2860
Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.
description
2016 nî lūn-bûn
@nan
2016 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2016 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
name
Opportunities and challenges i ...... rds data: a systematic review.
@ast
Opportunities and challenges i ...... rds data: a systematic review.
@en
type
label
Opportunities and challenges i ...... rds data: a systematic review.
@ast
Opportunities and challenges i ...... rds data: a systematic review.
@en
prefLabel
Opportunities and challenges i ...... rds data: a systematic review.
@ast
Opportunities and challenges i ...... rds data: a systematic review.
@en
P2093
P2860
P356
P1476
Opportunities and challenges i ...... rds data: a systematic review.
@en
P2093
Ann Marie Navar
Benjamin A Goldstein
Michael J Pencina
P2860
P304
P356
10.1093/JAMIA/OCW042
P577
2016-05-17T00:00:00Z