AIMC Topic: Electronic Health Records

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Using recurrent neural network models for early detection of heart failure onset.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We explored whether use of deep learning to model temporal relations among events in electronic health records (EHRs) would improve model performance in predicting initial diagnosis of heart failure (HF) compared to conventional methods th...

Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

Journal of patient safety
INTRODUCTION: The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electronic health record (EHR) from a mandatory, population-based patient safety reporting system.

Prediction of 30-Day All-Cause Readmissions in Patients Hospitalized for Heart Failure: Comparison of Machine Learning and Other Statistical Approaches.

JAMA cardiology
IMPORTANCE: Several attempts have been made at developing models to predict 30-day readmissions in patients with heart failure, but none have sufficient discriminatory capacity for clinical use. Machine-learning (ML) algorithms represent a novel appr...

Modeling a System for Generating Structured Reports.

Studies in health technology and informatics
The purpose of this research is to make the medical report generation process more practical, fast and reliable, both for the health professional and for the patient. We created an ontology and modeling of a structured report (SR) Standard DICOM SR.

Bringing Knowledge to Users in One Click: Infobuttons in the Problem List of an EHR.

Studies in health technology and informatics
The infobuttons allows the solving of information needs. In our study, the use of Infobuttons is described, analyzing the number of queries to UpToDate® from the problem list of an Electronic Health Record. There were 26419 requests in 8 months. The ...

Identifying Patients' Smoking Status from Electronic Dental Records Data.

Studies in health technology and informatics
Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessib...

Usability Evaluation of NLP-PIER: A Clinical Document Search Engine for Researchers.

Studies in health technology and informatics
NLP-PIER (Natural Language Processing - Patient Information Extraction for Research) is a self-service platform with a search engine for clinical researchers to perform natural language processing (NLP) queries using clinical notes. We conducted user...

Predicting Length of Stay for Obstetric Patients via Electronic Medical Records.

Studies in health technology and informatics
Obstetric care refers to the care provided to patients during ante-, intra-, and postpartum periods. Predicting length of stay (LOS) for these patients during their hospitalizations can assist healthcare organizations in allocating hospital resources...

An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria.

Studies in health technology and informatics
Eligibility criteria are important for clinical research protocols or clinical practice guidelines for determining who qualify for studies and to whom clinical evidence is applicable, but the free-text format is not amenable for computational process...