AIMC Topic: Electronic Health Records

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A machine learning model to predict therapeutic inertia in type 2 diabetes using electronic health record data.

Journal of endocrinological investigation
OBJECTIVE: To estimate the therapeutic inertia prevalence for patients with type 2 diabetes, develop and validate a machine learning model predicting therapeutic inertia, and determine the added predictive value of area-level social determinants of h...

Incorporation of quantitative imaging data using artificial intelligence improves risk prediction in veterans with liver disease.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Utilization of electronic health records data to derive predictive indexes such as the electronic Child-Turcotte-Pugh (eCTP) Score can have significant utility in health care delivery. Within the records, CT scans contain phenoty...

Using Natural Language Processing to Identify Stigmatizing Language in Labor and Birth Clinical Notes.

Maternal and child health journal
INTRODUCTION: Stigma and bias related to race and other minoritized statuses may underlie disparities in pregnancy and birth outcomes. One emerging method to identify bias is the study of stigmatizing language in the electronic health record. The obj...

Clinical Research Informatics: Contributions from 2022.

Yearbook of medical informatics
OBJECTIVES: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2022.

Knowledge Guided Feature Aggregation for the Prediction of Chronic Obstructive Pulmonary Disease With Chinese EMRs.

IEEE/ACM transactions on computational biology and bioinformatics
The automatic disease diagnosis utilizing clinical data has been suffering from the issues of feature sparse and high probability of missing values. Since the graph neural network is a effective tool to model the structural information and infer the ...

Use of Electronic Medical Records (EMR) in Gerontology: Benefits, Considerations and a Promising Future.

Clinical interventions in aging
Electronic medical records (EMRs) have many benefits in clinical research in gerontology, enabling data analysis, development of prognostic tools and disease risk prediction. EMRs also offer a range of advantages in clinical practice, such as compreh...

Use of Natural Language Processing to Identify Sexual and Reproductive Health Information in Clinical Text.

Methods of information in medicine
OBJECTIVES: This study aimed to enable clinical researchers without expertise in natural language processing (NLP) to extract and analyze information about sexual and reproductive health (SRH), or other sensitive health topics, from large sets of cli...

De-identification of free text data containing personal health information: a scoping review of reviews.

International journal of population data science
INTRODUCTION: Using data in research often requires that the data first be de-identified, particularly in the case of health data, which often include Personal Identifiable Information (PII) and/or Personal Health Identifying Information (PHII). Ther...

Fusion Modeling: Combining Clinical and Imaging Data to Advance Cardiac Care.

Circulation. Cardiovascular imaging
In addition to the traditional clinical risk factors, an increasing amount of imaging biomarkers have shown value for cardiovascular risk prediction. Clinical and imaging data are captured from a variety of data sources during multiple patient encoun...

Attention-based neural networks for clinical prediction modelling on electronic health records.

BMC medical research methodology
BACKGROUND: Deep learning models have had a lot of success in various fields. However, on structured data they have struggled. Here we apply four state-of-the-art supervised deep learning models using the attention mechanism and compare against logis...