AIMC Topic: International Classification of Diseases

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Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

Methods of information in medicine Jul 14, 2021
OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients fr...
Humans Algorithms Asthma Adolescent Phenotype Electronic Health Records International Classification of Diseases Child, Preschool Child Natural Language Processing
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Establishing a carotid artery stenosis disease cohort for comparative effectiveness research using natural language processing.

Journal of vascular surgery Jun 25, 2021
OBJECTIVE: Investigation of asymptomatic carotid stenosis treatment is hindered by the lack of a contemporary population-based disease cohort. We describe the use of natural language processing (NLP) to identify stenosis in patients undergoing caroti...
Natural Language Processing Data Mining Ultrasonography, Doppler California Severity of Illness Index Hemodynamics Predictive Value of Tests Asymptomatic Diseases Computed Tomography Angiography Carotid Stenosis Comparative Effectiveness Research International Classification of Diseases Magnetic Resonance Angiography Medical Records Retrospective Studies Cross-Sectional Studies Humans
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A comparison of natural language processing to ICD-10 codes for identification and characterization of pulmonary embolism.

Thrombosis research May 6, 2021
INTRODUCTION: The 10th revision of the International Classification of Diseases (ICD-10) codes is frequently used to identify pulmonary embolism (PE) events, although the validity of ICD-10 has been questioned. Natural language processing (NLP) is a ...
Retrospective Studies International Classification of Diseases Natural Language Processing Humans Pulmonary Embolism Algorithms
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Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach.

Scientific reports Apr 14, 2021
Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healt...
Humans Neural Networks, Computer Databases, Factual Male Middle Aged Comorbidity Renal Insufficiency, Chronic Female Aged Aged, 80 and over Risk Myocardial Infarction Cardiomyopathies International Classification of Diseases Veterans
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GHS-NET a generic hybridized shallow neural network for multi-label biomedical text classification.

Journal of biomedical informatics Feb 15, 2021
Exponential growth of biomedical literature and clinical data demands more robust yet precise computational methodologies to extract useful insights from biomedical literature and to perform accurate assignment of disease-specific codes. Such approac...
International Classification of Diseases Neural Networks, Computer Deep Learning Computational Biology
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Selection of Clinical Text Features for Classifying Suicide Attempts.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Research has demonstrated cohort misclassification when studies of suicidal thoughts and behaviors (STBs) rely on ICD-9/10-CM diagnosis codes. Electronic health record (EHR) data are being explored to better identify patients, a process called EHR ph...
International Classification of Diseases Male Natural Language Processing Phenotype Prevalence Cohort Studies Humans Data Mining Electronic Health Records Suicide, Attempted ROC Curve Machine Learning Female Algorithms
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Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably.

Journal of clinical epidemiology Jan 22, 2021
OBJECTIVE: The objective of the study was to compare the performance of logistic regression and boosted trees for predicting patient mortality from large sets of diagnosis codes in electronic healthcare records.
Logistic Models Age Factors Myocardial Infarction International Classification of Diseases Mortality Sex Factors Hip Fractures Colorectal Neoplasms Male Middle Aged England Female Aged Aged, 80 and over Humans Forecasting Machine Learning Electronic Health Records
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Applying Convolutional Neural Networks to Predict the ICD-9 Codes of Medical Records.

Sensors (Basel, Switzerland) Dec 11, 2020
The International Statistical Classification of Disease and Related Health Problems (ICD) is an international standard system for categorizing and reporting diseases, injuries, disorders, and health conditions. Most previously-proposed disease predic...
Electronic Health Records Deep Learning International Classification of Diseases Humans Neural Networks, Computer Algorithms
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Identification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Oct 15, 2020
INTRODUCTION: Nontraumatic intracranial hemorrhage (ICH) is a neurological emergency of research interest; however, unlike ischemic stroke, has not been well studied in large datasets due to the lack of an established administrative claims-based defi...
Data Mining Reproducibility of Results Intracranial Hemorrhages Middle Aged Administrative Claims, Healthcare Aged, 80 and over Humans International Classification of Diseases Aged Support Vector Machine Male Phenotype Health Services Research Predictive Value of Tests Female
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Time Series Analysis and Forecasting with Automated Machine Learning on a National ICD-10 Database.

International journal of environmental research and public health Jul 10, 2020
The application of machine learning (ML) for use in generating insights and making predictions on new records continues to expand within the medical community. Despite this progress to date, the application of time series analysis has remained undere...
Forecasting Databases, Factual International Classification of Diseases Romania Humans Machine Learning
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