AIMC Topic: Electronic Health Records

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Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports.

Journal of the American College of Radiology : JACR
PURPOSE: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations.

Categorization of free-text drug orders using character-level recurrent neural networks.

International journal of medical informatics
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 ...

Interpretable deep learning to map diagnostic texts to ICD-10 codes.

International journal of medical informatics
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...

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
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...

Using a Multi-Task Recurrent Neural Network With Attention Mechanisms to Predict Hospital Mortality of Patients.

IEEE journal of biomedical and health informatics
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...

Smoothing dense spaces for improved relation extraction between drugs and adverse reactions.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: This work aims at extracting Adverse Drug Reactions (ADRs), i.e. a harm directly caused by a drug at normal doses, from Electronic Health Records (EHRs). The lack of readily available EHRs because of confidentiality issues a...

Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing.

International journal of medical informatics
BACKGROUND: The management of hypertrophic cardiomyopathy (HCM) patients requires the knowledge of risk factors associated with sudden cardiac death (SCD). SCD risk factors such as syncope and family history of SCD (FH-SCD) as well as family history ...

A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard.

BMC medical informatics and decision making
BACKGROUND: Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historical electronic health record (...