AIMC Topic: Electronic Health Records

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Deep Sequential Models for Suicidal Ideation From Multiple Source Data.

IEEE journal of biomedical and health informatics May 27, 2019
This paper presents a novel method for predicting suicidal ideation from electronic health records (EHR) and ecological momentary assessment (EMA) data using deep sequential models. Both EHR longitudinal data and EMA question forms are defined by asy...
Suicide Models, Psychological Ecological Momentary Assessment Deep Learning Suicide Prevention Suicidal Ideation Humans Neural Networks, Computer Electronic Health Records Female Adult Male Middle Aged
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An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes.

Computer methods and programs in biomedicine May 25, 2019
BACKGROUND AND OBJECTIVE: Code assignment is of paramount importance in many levels in modern hospitals, from ensuring accurate billing process to creating a valid record of patient care history. However, the coding process is tedious and subjective,...
Models, Statistical Regression Analysis Critical Care Medical Informatics International Classification of Diseases Intensive Care Units Electronic Health Records Reproducibility of Results Deep Learning Humans Neural Networks, Computer Algorithms
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Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer.

International journal of medical informatics May 25, 2019
BACKGROUND: Hospital discharge summaries offer a potentially rich resource to enhance pharmacovigilance efforts to evaluate drug safety in real-world clinical practice. However, it is infeasible for experts to read through all discharge summaries to ...
Humans Medical Errors Machine Learning Singapore Patient Discharge Drug-Related Side Effects and Adverse Reactions Algorithms Adverse Drug Reaction Reporting Systems Electronic Health Records Natural Language Processing
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Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports.

Journal of the American College of Radiology : JACR May 24, 2019
PURPOSE: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations.
Radiology Research Report Incidental Findings United States Solitary Pulmonary Nodule Natural Language Processing Retrospective Studies Tomography, X-Ray Computed Electronic Health Records Female Reproducibility of Results Male Cohort Studies Humans
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Categorization of free-text drug orders using character-level recurrent neural networks.

International journal of medical informatics May 23, 2019
BACKGROUND AND PURPOSE: Manual annotation and categorization of non-standardized text ("free-text") of drug orders entered into electronic health records is a labor-intensive task. However, standardization is required for drug order analyses and has ...
Deep Learning Decision Support Systems, Clinical Support Vector Machine Neural Networks, Computer Machine Learning Electronic Health Records
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Interpretable deep learning to map diagnostic texts to ICD-10 codes.

International journal of medical informatics May 22, 2019
BACKGROUND: Automatic extraction of morbid disease or conditions contained in Death Certificates is a critical process, useful for billing, epidemiological studies and comparison across countries. The fact that these clinical documents are written in...
Neural Networks, Computer International Classification of Diseases Electronic Health Records Deep Learning
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Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processing.

Epilepsia May 21, 2019
OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is an important cause of mortality in epilepsy. However, there is a gap in how often providers counsel patients about SUDEP. One potential solution is to electronically prompt clinicians to provi...
Humans Sensitivity and Specificity Cross-Sectional Studies Natural Language Processing Data Interpretation, Statistical Algorithms Retrospective Studies Electronic Health Records Risk Factors Death, Sudden Epilepsy, Tonic-Clonic Sudden Unexpected Death in Epilepsy Epilepsy Neurosurgery Drug Resistant Epilepsy
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Automating Ischemic Stroke Subtype Classification Using Machine Learning and Natural Language Processing.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association May 15, 2019
OBJECTIVE: The manual adjudication of disease classification is time-consuming, error-prone, and limits scaling to large datasets. In ischemic stroke (IS), subtype classification is critical for management and outcome prediction. This study sought to...
Data Mining Brain Ischemia Automation Pattern Recognition, Automated Natural Language Processing Registries Machine Learning Stroke Electronic Health Records Female Aged Reproducibility of Results Aged, 80 and over Humans Male Middle Aged
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Using a Multi-Task Recurrent Neural Network With Attention Mechanisms to Predict Hospital Mortality of Patients.

IEEE journal of biomedical and health informatics May 13, 2019
Estimating hospital mortality of patients is important in assisting clinicians to make decisions and hospital providers to allocate resources. This paper proposed a multi-task recurrent neural network with attention mechanisms to predict patients' ho...
Aged Male Middle Aged Humans Hospital Mortality Neural Networks, Computer Electronic Health Records Female
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A machine learning approach for predicting urine output after fluid administration.

Computer methods and programs in biomedicine May 13, 2019
BACKGROUND AND OBJECTIVE: To develop a machine learning model to predict urine output (UO) in sepsis patients after fluid resuscitation.
Aged Sensitivity and Specificity Male Middle Aged Fluid Therapy Humans Sepsis Electronic Health Records Critical Care Decision Support Systems, Clinical Female Machine Learning Kidney Function Tests Urination Risk Factors Algorithms Area Under Curve Resuscitation Intensive Care Units
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