AIMC Topic: Utah

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Predicting bullying victimization among adolescents using the risk and protective factor framework: a large-scale machine learning approach.

BMC public health Jan 25, 2025
BACKGROUND: Bullying, encompassing physical, psychological, social, or educational harm, affects approximately 1 in 20 United States teens aged 12-18. The prevalence and impact of bullying, including online bullying, necessitate a deeper understandin...
Humans Machine Learning Female Risk Factors Child Utah Bullying Protective Factors Crime Victims Male Students Surveys and Questionnaires Adolescent
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Predicting suicidal thoughts and behavior among adolescents using the risk and protective factor framework: A large-scale machine learning approach.

PloS one Nov 3, 2021
INTRODUCTION: Addressing the problem of suicidal thoughts and behavior (STB) in adolescents requires understanding the associated risk factors. While previous research has identified individual risk and protective factors associated with many adolesc...
Bullying Internet Schools Cannabis Utah Young Adult Humans Surveys and Questionnaires Male Machine Learning Adolescent Students Forecasting Suicide Prevention Female Suicide, Attempted Suicidal Ideation Risk Factors Suicide
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Development of a Portable Tool to Identify Patients With Atrial Fibrillation Using Clinical Notes From the Electronic Medical Record.

Circulation. Cardiovascular quality and outcomes Oct 14, 2020
BACKGROUND: The electronic medical record contains a wealth of information buried in free text. We created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone.
Humans Electronic Health Records Male Middle Aged Prevalence Diagnosis, Computer-Assisted Predictive Value of Tests Female Reproducibility of Results Aged Aged, 80 and over Natural Language Processing Atrial Fibrillation Utah Chicago
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Determination of Marital Status of Patients from Structured and Unstructured Electronic Healthcare Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Social Determinants of Health, including marital status, are becoming increasingly identified as key drivers of health care utilization. This paper describes a robust method to determine the marital status of patients using structured and unstructure...
Social Determinants of Health Utah Humans Male Machine Learning Natural Language Processing Electronic Health Records Hospitals, University Female Marital Status
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Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology Feb 25, 2020
BACKGROUND: Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking-related behaviors that may concentrate in some families. We demonstrate a novel ...
Utah Pedigree Neoplastic Syndromes, Hereditary Urinary Bladder Neoplasms Data Mining Data Collection Genetic Heterogeneity Aged, 80 and over Young Adult Adult Male Middle Aged Risk Assessment Adolescent Incidence Genetic Predisposition to Disease Databases, Factual Female Risk Factors Aged Humans Machine Learning
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Scaling-up NLP Pipelines to Process Large Corpora of Clinical Notes.

Methods of information in medicine Nov 4, 2015
INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare".
Risk Assessment Prevalence Decision Support Systems, Clinical Urinary Catheterization Humans Natural Language Processing Urinary Tract Infections Machine Learning Catheter-Related Infections Data Mining Algorithms Electronic Health Records Hospitals, Veterans Datasets as Topic Vocabulary, Controlled Utah
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Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes.

Journal of biomedical informatics Aug 28, 2015
The 2014 i2b2 natural language processing shared task focused on identifying cardiovascular risk factors such as high blood pressure, high cholesterol levels, obesity and smoking status among other factors found in health records of diabetic patients...
Female Aged Male Cardiovascular Diseases Middle Aged Risk Assessment Diabetes Complications Comorbidity Incidence Cohort Studies Data Mining Humans Utah Electronic Health Records Longitudinal Studies Pattern Recognition, Automated Narration Computer Security Natural Language Processing Vocabulary, Controlled Confidentiality
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Acceptability and Perceived Utility of Telemedical Consultation during Cardiac Arrest Resuscitation. A Multicenter Survey.

Annals of the American Thoracic Society Mar 1, 2020
Many clinicians who participate in or lead in-hospital cardiac arrest (IHCA) resuscitations lack confidence for this task or worry about errors. Well-led IHCA resuscitation teams deliver better care, but expert resuscitation leaders are often unavai...
Heart Arrest Nursing Staff, Hospital Hospital Units Female Humans Idaho Telemedicine Adult Intensive Care Units Medical Staff, Hospital Referral and Consultation Male Utah Middle Aged Cardiopulmonary Resuscitation Attitude of Health Personnel
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These scientists are setting a forest on fire - and studying it with drones.

Nature May 1, 2019
California Forestry Humans Models, Theoretical Environmental Monitoring Robotics Fires Wildfires Utah Research Personnel
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