AIMC Topic: Veterans Health
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Artificial intelligence approaches for phenotyping heart failure in U.S. Veterans Health Administration electronic health record.
ESC heart failure
Jun 14, 2024
AIMS: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes....
Leveraging Natural Language Processing to Improve Electronic Health Record Suicide Risk Prediction for Veterans Health Administration Users.
The Journal of clinical psychiatry
Jun 19, 2023
Suicide risk prediction models frequently rely on structured electronic health record (EHR) data, including patient demographics and health care usage variables. Unstructured EHR data, such as clinical notes, may improve predictive accuracy by allow...
Trends in Robot-Assisted Procedures for General Surgery in the Veterans Health Administration.
The Journal of surgical research
Aug 12, 2022
INTRODUCTION: Implementation of robot-assisted procedures is growing. Utilization within the country's largest healthcare network, the Veterans Health Administration, is unclear.
Robot-Assisted General Surgery Procedures at the Veterans Health Administration: A Comparison of Surgical Techniques.
The Journal of surgical research
Jul 8, 2022
INTRODUCTION: The use of the robot in general surgery has exploded in the last decade. The Veterans Health Administration presents a unique opportunity to study differences between surgical approaches due to the ability to control for health system a...
Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration.
Annual review of biomedical data science
May 24, 2022
Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by elec...
Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization.
Chiropractic & manual therapies
Jul 17, 2020
BACKGROUND: Chronic spinal pain conditions affect millions of US adults and carry a high healthcare cost burden, both direct and indirect. Conservative interventions for spinal pain conditions, including chiropractic care, have been associated with l...
Applying Machine Learning to Linked Administrative and Clinical Data to Enhance the Detection of Homelessness among Vulnerable Veterans.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
U.S. military veterans who were discharged from service for misconduct are at high risk for homelessness. Stratifying homelessness risk based on both military service factors and clinical characteristics could facilitate targeted provision of prevent...
Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.
Digestive diseases and sciences
Aug 31, 2017
INTRODUCTION: Natural language processing is a powerful technique of machine learning capable of maximizing data extraction from complex electronic medical records.
Knowledge mapping visualization analysis of the military health and medicine papers published in the web of science over the past 10 years.
Military Medical Research
Jul 12, 2017
BACKGROUND: Military medicine is a research field that seeks to solve the medical problems that occur in modern war conditions based on public medicine theory.
Unlocking echocardiogram measurements for heart disease research through natural language processing.
BMC cardiovascular disorders
Jun 12, 2017
BACKGROUND: In order to investigate the mechanisms of cardiovascular disease in HIV infected and uninfected patients, an analysis of echocardiogram reports is required for a large longitudinal multi-center study.
Data Mining
Retrospective Studies
Automation
Reproducibility of Results
Humans
Pattern Recognition, Automated
Ventricular Function, Left
Databases, Factual
Terminology as Topic
Predictive Value of Tests
Stroke Volume
Veterans Health
Echocardiography
Natural Language Processing
Software Validation
Feasibility Studies
HIV Infections
Heart Failure
Longitudinal Studies
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