AIMC Topic: Electronic Health Records

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Recurrent Neural Networks for Early Detection of Heart Failure From Longitudinal Electronic Health Record Data: Implications for Temporal Modeling With Respect to Time Before Diagnosis, Data Density, Data Quantity, and Data Type.

Circulation. Cardiovascular quality and outcomes Oct 15, 2019
BACKGROUND: We determined the impact of data volume and diversity and training conditions on recurrent neural network methods compared with traditional machine learning methods.
Longitudinal Studies Predictive Value of Tests Heart Failure Early Diagnosis Diagnosis, Computer-Assisted Incidence Time Factors Primary Health Care Smoking Alcohol Drinking California Vital Signs Humans Neural Networks, Computer Machine Learning Electronic Health Records Female Reproducibility of Results Risk Factors Male
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Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis.

Circulation. Cardiovascular quality and outcomes Oct 15, 2019
BACKGROUND: Atrial fibrillation (AF) increases the risk of stroke 5-fold and there is rising interest to determine if AF severity or burden can further risk stratify these patients, particularly for near-term events. Using continuous remote monitorin...
Humans Neural Networks, Computer Machine Learning Prognosis Aged Risk Assessment Veterans Health Services Aged, 80 and over Diagnosis, Computer-Assisted Male Retrospective Studies Time Factors Middle Aged Atrial Fibrillation Electronic Health Records Logistic Models United States Proof of Concept Study Female Administrative Claims, Healthcare Predictive Value of Tests Risk Factors Telemetry Signal Processing, Computer-Assisted Stroke
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Comparing information extraction techniques for low-prevalence concepts: The case of insulin rejection by patients.

Journal of biomedical informatics Oct 13, 2019
OBJECTIVE: To comparatively evaluate a range of Natural Language Processing (NLP) approaches for Information Extraction (IE) of low-prevalence concepts in clinical notes on the example of decline of insulin therapy recommendation by patients.
Support Vector Machine Natural Language Processing Data Mining Treatment Refusal User-Computer Interface Insulin Hypoglycemic Agents Diabetes Mellitus Humans Neural Networks, Computer Electronic Health Records
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Deep representation learning for individualized treatment effect estimation using electronic health records.

Journal of biomedical informatics Oct 11, 2019
Utilizing clinical observational data to estimate individualized treatment effects (ITE) is a challenging task, as confounding inevitably exists in clinical data. Most of the existing models for ITE estimation tackle this problem by creating unbiased...
Humans Algorithms Prognosis Electronic Health Records Deep Learning Heart Failure Datasets as Topic
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Identification of postoperative complications using electronic health record data and machine learning.

American journal of surgery Oct 9, 2019
BACKGROUND: Using the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) complication status of patients who underwent an operation at the University of Colorado Hospital, we developed a machine learning algorithm for ...
Aged Humans Algorithms Predictive Value of Tests Postoperative Complications Machine Learning Quality Improvement Adult Databases, Factual ROC Curve Male United States Electronic Health Records Middle Aged Models, Statistical Female
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A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis.

International journal of medical informatics Oct 5, 2019
CONTEXT: Adverse events in healthcare are often collated in incident reports which contain unstructured free text. Learning from these events may improve patient safety. Natural language processing (NLP) uses computational techniques to interrogate f...
Natural Language Processing Risk Management Drug-Related Side Effects and Adverse Reactions Adverse Drug Reaction Reporting Systems Humans Electronic Health Records
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Aggregating the syntactic and semantic similarity of healthcare data towards their transformation to HL7 FHIR through ontology matching.

International journal of medical informatics Oct 5, 2019
BACKGROUND AND OBJECTIVE: Healthcare systems deal with multiple challenges in releasing information from data silos, finding it almost impossible to be implemented, maintained and upgraded, with difficulties ranging in the technical, security and hum...
Information Dissemination Semantics Biological Ontologies Humans Vocabulary, Controlled Systems Integration Algorithms Delivery of Health Care Electronic Health Records Health Level Seven
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A frame semantic overview of NLP-based information extraction for cancer-related EHR notes.

Journal of biomedical informatics Oct 4, 2019
OBJECTIVE: There is a lot of information about cancer in Electronic Health Record (EHR) notes that can be useful for biomedical research provided natural language processing (NLP) methods are available to extract and structure this information. In th...
Humans Electronic Health Records Neoplasms Natural Language Processing Semantics
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Predicting post-stroke pneumonia using deep neural network approaches.

International journal of medical informatics Oct 1, 2019
BACKGROUND AND PURPOSE: Pneumonia is a common complication after stroke, causing an increased length of hospital stay and death. Therefore, the timely and accurate prediction of post-stroke pneumonia would be highly valuable in clinical practice. Pre...
Female Hospitalization Aged Aged, 80 and over Male Middle Aged China ROC Curve Humans Machine Learning Algorithms Electronic Health Records Pneumonia Predictive Value of Tests Stroke Brain Ischemia
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Validation of an alcohol misuse classifier in hospitalized patients.

Alcohol (Fayetteville, N.Y.) Sep 28, 2019
BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have limitations, including low sensitivity. Information in the clinical notes of the electronic health reco...
Case-Control Studies Adult Supervised Machine Learning Humans Sensitivity and Specificity Inpatients Alcoholism Male Electronic Health Records Natural Language Processing Middle Aged Tertiary Care Centers Female Reproducibility of Results
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