AIMC Topic: Electronic Health Records

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Explainable deep learning in healthcare: A methodological survey from an attribution view.

WIREs mechanisms of disease Jan 17, 2022
The increasing availability of large collections of electronic health record (EHR) data and unprecedented technical advances in deep learning (DL) have sparked a surge of research interest in developing DL based clinical decision support systems for ...
Deep Learning Surveys and Questionnaires Delivery of Health Care Electronic Health Records Artificial Intelligence
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A Knowledge Distillation Ensemble Framework for Predicting Short- and Long-Term Hospitalization Outcomes From Electronic Health Records Data.

IEEE journal of biomedical and health informatics Jan 17, 2022
The ability to perform accurate prognosis is crucial for proactive clinical decision making, informed resource management and personalised care. Existing outcome prediction models suffer from a low recall of infrequent positive outcomes. We present a...
Humans Hospitalization Length of Stay ROC Curve Retrospective Studies Electronic Health Records Machine Learning
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Using Machine Learning to Evaluate the Role of Microinflammation in Cardiovascular Events in Patients With Chronic Kidney Disease.

Frontiers in immunology Jan 10, 2022
BACKGROUND: Lipid metabolism disorder, as one major complication in patients with chronic kidney disease (CKD), is tied to an increased risk for cardiovascular disease (CVD). Traditional lipid-lowering statins have been found to have limited benefit ...
Renal Insufficiency, Chronic C-Reactive Protein Female Cholesterol Hydroxymethylglutaryl-CoA Reductase Inhibitors Middle Aged Risk Factors Machine Learning Inflammation Male Humans Retrospective Studies Aged Cardiovascular Diseases Neural Networks, Computer Electronic Health Records
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Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing.

Journal of biomedical informatics Jan 7, 2022
OBJECTIVE: Social determinants of health (SDOH) are non-medical factors that can profoundly impact patient health outcomes. However, SDOH are rarely available in structured electronic health record (EHR) data such as diagnosis codes, and more commonl...
Retrospective Studies Electronic Health Records Natural Language Processing Social Determinants of Health Deep Learning Humans
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Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients.

PloS one Jan 6, 2022
Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and efficient utilization of resources. Accessibility of electronic health records (EHR) has enabled data-driven predictive modeling using machine learning....
Databases, Factual Intensive Care Units Electronic Health Records Humans Machine Learning ROC Curve Logistic Models Area Under Curve Length of Stay Hospital Mortality
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Postoperative delirium prediction using machine learning models and preoperative electronic health record data.

BMC anesthesiology Jan 3, 2022
BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) d...
Reproducibility of Results Delirium Aged Middle Aged Postoperative Complications Male Retrospective Studies Electronic Health Records Female Humans Machine Learning Cohort Studies Predictive Value of Tests Preoperative Period
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Multi-task learning for Chinese clinical named entity recognition with external knowledge.

BMC medical informatics and decision making Dec 31, 2021
BACKGROUND: Named entity recognition (NER) on Chinese electronic medical/healthcare records has attracted significantly attentions as it can be applied to building applications to understand these records. Most previous methods have been purely data-...
China Humans Neural Networks, Computer Attention Electronic Health Records Names
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Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances.

Informatics for health & social care Dec 30, 2021
We derived machine learning models utilizing features generated by natural language processing (NLP) of free-text data from an ambulance services provider to identify fall cases. The data comprised samples of electronic patient care records care reco...
Humans Machine Learning Natural Language Processing Patient Care Electronic Health Records Electronics Ambulances
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Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies.

Journal of biomedical informatics Dec 30, 2021
OBJECTIVE: Temporal electronic health records (EHRs) contain a wealth of information for secondary uses, such as clinical events prediction and chronic disease management. However, challenges exist for temporal data representation. We therefore sough...
Deep Learning PubMed Electronic Health Records
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A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study.

Journal of medical Internet research Dec 27, 2021
BACKGROUND: Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, somewhat improves the process of ED treat...
Hospitalization Deep Learning Humans Electronic Health Records Prospective Studies Triage Emergency Service, Hospital Retrospective Studies
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