AIMC Topic: Electronic Health Records

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Ensemble method-based extraction of medication and related information from clinical texts.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: Accurate and complete information about medications and related information is crucial for effective clinical decision support and precise health care. Recognition and reduction of adverse drug events is also central to effective patient c...
Humans Algorithms Electronic Health Records Information Storage and Retrieval Narration Natural Language Processing Drug-Related Side Effects and Adverse Reactions
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An ensemble of neural models for nested adverse drug events and medication extraction with subwords.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: This article describes an ensembling system to automatically extract adverse drug events and drug related entities from clinical narratives, which was developed for the 2018 n2c2 Shared Task Track 2.
Humans Neural Networks, Computer Electronic Health Records Information Storage and Retrieval Narration Natural Language Processing Drug-Related Side Effects and Adverse Reactions
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Leveraging Electronic Health Records and Machine Learning to Tailor Nursing Care for Patients at High Risk for Readmissions.

Journal of nursing care quality Jan 1, 2020
BACKGROUND: Electronic health record-derived data and novel analytics, such as machine learning, offer promising approaches to identify high-risk patients and inform nursing practice.
Data Analysis Humans Retrospective Studies Machine Learning Electronic Health Records Aged Female Male Risk Factors Nursing Care Middle Aged Risk Management Patient Readmission
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A study of deep learning approaches for medication and adverse drug event extraction from clinical text.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: This article presents our approaches to extraction of medications and associated adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 National NLP Clinical Challenges (n2c2) shared task.
Humans Machine Learning Algorithms Natural Language Processing Pharmaceutical Preparations Drug-Related Side Effects and Adverse Reactions Information Storage and Retrieval Electronic Health Records Deep Learning Narration
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Can AI Fix Medical Records?

Nature Dec 1, 2019
Medical Informatics Applications Adult Appendicitis Humans Male Privacy Medication Errors Medical History Taking Artificial Intelligence User-Computer Interface Information Dissemination Health Care Surveys Electronic Health Records Drug Prescriptions
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Extracting entities with attributes in clinical text via joint deep learning.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: Extracting clinical entities and their attributes is a fundamental task of natural language processing (NLP) in the medical domain. This task is typically recognized as 2 sequential subtasks in a pipeline, clinical entity or attribute reco...
Deep Learning Natural Language Processing Data Mining Datasets as Topic Humans Electronic Health Records
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What health records data are required for accurate prediction of suicidal behavior?

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.
Suicide Logistic Models Self Report Models, Psychological Suicide, Attempted Surveys and Questionnaires Adolescent Male Middle Aged Risk Assessment Female Humans Risk Factors Machine Learning Aged Electronic Health Records Adult
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The machine giveth and the machine taketh away: a parrot attack on clinical text deidentified with hiding in plain sight.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: Clinical corpora can be deidentified using a combination of machine-learned automated taggers and hiding in plain sight (HIPS) resynthesis. The latter replaces detected personally identifiable information (PII) with random surrogates, allo...
Machine Learning Delivery of Health Care Humans Ambulatory Care Facilities Electronic Health Records Computer Security Washington Confidentiality Personally Identifiable Information Data Anonymization
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Neural machine translation of clinical texts between long distance languages.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: To analyze techniques for machine translation of electronic health records (EHRs) between long distance languages, using Basque and Spanish as a reference. We studied distinct configurations of neural machine translation systems and used d...
Humans Neural Networks, Computer Electronic Health Records Translating Terminology as Topic Spain Natural Language Processing Systematized Nomenclature of Medicine
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Assessing clinical heterogeneity in sepsis through treatment patterns and machine learning.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: To use unsupervised topic modeling to evaluate heterogeneity in sepsis treatment patterns contained within granular data of electronic health records.
Quality of Health Care Hospital Mortality Unsupervised Machine Learning Patient Acuity Hospitalization Aged Aged, 80 and over Middle Aged Sepsis Adult Male Retrospective Studies Electronic Health Records Female Humans Anti-Bacterial Agents
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