AIMC Journal:
Journal of the American Medical Informatics Association : JAMIA

Showing 341 to 350 of 493 articles

A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2020
OBJECTIVE: The Unified Medical Language System (UMLS) integrates various source terminologies to support interoperability between biomedical information systems. In this article, we introduce a novel transformation-based auditing method that leverage...
Systematized Nomenclature of Medicine Terminology as Topic Unified Medical Language System Gene Ontology Language Quality Improvement
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Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)-based ranking for concept normalization.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2020
OBJECTIVE: Concept normalization, the task of linking phrases in text to concepts in an ontology, is useful for many downstream tasks including relation extraction, information retrieval, etc. We present a generate-and-rank concept normalization syst...
RxNorm Systematized Nomenclature of Medicine Unified Medical Language System Patient Discharge Summaries Neural Networks, Computer Natural Language Processing Humans
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Can Unified Medical Language System-based semantic representation improve automated identification of patient safety incident reports by type and severity?

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2020
OBJECTIVE: The study sought to evaluate the feasibility of using Unified Medical Language System (UMLS) semantic features for automated identification of reports about patient safety incidents by type and severity.
Humans Patient Safety Datasets as Topic Semantics Unified Medical Language System Medical Errors Support Vector Machine Natural Language Processing Risk Management
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Fold-stratified cross-validation for unbiased and privacy-preserving federated learning.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2020
OBJECTIVE: We introduce fold-stratified cross-validation, a validation methodology that is compatible with privacy-preserving federated learning and that prevents data leakage caused by duplicates of electronic health records (EHRs).
Humans Machine Learning Confidentiality Data Anonymization Algorithms Electronic Health Records Computer Security
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sureLDA: A multidisease automated phenotyping method for the electronic health record.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2020
OBJECTIVE: A major bottleneck hindering utilization of electronic health record data for translational research is the lack of precise phenotype labels. Chart review as well as rule-based and supervised phenotyping approaches require laborious expert...
Natural Language Processing Translational Research, Biomedical Humans Precision Medicine Algorithms Electronic Health Records ROC Curve
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Constructing co-occurrence network embeddings to assist association extraction for COVID-19 and other coronavirus infectious diseases.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2020
OBJECTIVE: As coronavirus disease 2019 (COVID-19) started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for having a knowledge repository for the disease became crucial. To address this issue, a new COVID-19 m...
Coronavirus Infections Datasets as Topic Pneumonia, Viral Support Vector Machine Decision Trees Humans Algorithms Bayes Theorem ROC Curve Pandemics Logistic Models Neural Networks, Computer COVID-19 Software
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An artificial intelligence approach to COVID-19 infection risk assessment in virtual visits: A case report.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2020
OBJECTIVE: In an effort to improve the efficiency of computer algorithms applied to screening for coronavirus disease 2019 (COVID-19) testing, we used natural language processing and artificial intelligence-based methods with unstructured patient dat...
Electronic Health Records SARS-CoV-2 Risk Assessment Pandemics COVID-19 Algorithms Coronavirus Infections Telemedicine COVID-19 Testing Organizational Case Studies Deep Learning ROC Curve Natural Language Processing Humans Neural Networks, Computer Artificial Intelligence Pneumonia, Viral Clinical Laboratory Techniques South Carolina Betacoronavirus
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Generating sequential electronic health records using dual adversarial autoencoder.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Recent studies on electronic health records (EHRs) started to learn deep generative models and synthesize a huge amount of realistic records, in order to address significant privacy issues surrounding the EHR. However, most of them only fo...
Confidentiality Software Humans Computer Simulation Electronic Health Records Neural Networks, Computer Machine Learning
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Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Machine learning models trained on electronic health records have achieved high prognostic accuracy in test datasets, but little is known about their embedding into clinical workflows. We implemented a random forest-based algorithm to iden...
Humans Aged, 80 and over Machine Learning Male Female Algorithms Risk Assessment Workflow Middle Aged Hospitalization Prospective Studies Delirium ROC Curve Electronic Health Records Aged Models, Theoretical
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Predicting complications of diabetes mellitus using advanced machine learning algorithms.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: We sought to predict if patients with type 2 diabetes mellitus (DM2) would develop 10 selected complications. Accurate prediction of complications could help with more targeted measures that would prevent or slow down their development.
Diabetes Complications Humans Neural Networks, Computer Deep Learning Diabetes Mellitus, Type 2 Decision Trees Algorithms Prognosis Risk Assessment
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