AIMC Topic: Electronic Health Records

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Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges.

PharmacoEconomics
Combinations of healthcare claims data with additional datasets provide large and rich sources of information. The dimensionality and complexity of these combined datasets can be challenging to handle with standard statistical analyses. However, rece...

Quantifying risk factors in medical reports with a context-aware linear model.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We seek to quantify the mortality risk associated with mentions of medical concepts in textual electronic health records (EHRs). Recognizing mentions of named entities of relevant types (eg, conditions, symptoms, laboratory tests or behavi...

A Deep Learning-Based Decision Support Tool for Precision Risk Assessment of Breast Cancer.

JCO clinical cancer informatics
PURPOSE: The Breast Imaging Reporting and Data System (BI-RADS) lexicon was developed to standardize mammographic reporting to assess cancer risk and facilitate the decision to biopsy. Because of substantial interobserver variability in the applicati...

An outcome model approach to transporting a randomized controlled trial results to a target population.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to transport RCT results to target populations has focused on weighting RCT data to look like the tar...

Natural Language Processing for Automated Quantification of Brain Metastases Reported in Free-Text Radiology Reports.

JCO clinical cancer informatics
PURPOSE: Although the bulk of patient-generated health data are increasing exponentially, their use is impeded because most data come in unstructured format, namely as free-text clinical reports. A variety of natural language processing (NLP) methods...

Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information doc...

Medical assertion classification in Chinese EMRs using attention enhanced neural network.

Mathematical biosciences and engineering : MBE
Electronic medical records (EMRs), such as hospital discharge summaries, contain a wealth of information only expressed in natural language. Automated methods for extracting information from these records must be able to recognize medical concepts in...

Predicting Future Cardiovascular Events in Patients With Peripheral Artery Disease Using Electronic Health Record Data.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Patients with peripheral artery disease (PAD) are at risk of major adverse cardiac and cerebrovascular events. There are no readily available risk scores that can accurately identify which patients are most likely to sustain an event, mak...