AIMC Topic: Washington

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A Public Dataset of Annotated Orcinus orca Acoustic Signals for Detection and Ecotype Classification.

Scientific data Jul 3, 2025
Killer whales (Orcinus orca) exhibit significant ecological and genetic diversity, with three primary sympatric populations in the Northeast Pacific: Resident, Bigg's (Transient), and Offshore. Each population is characterized by distinct foraging ha...
British Columbia Washington Alaska Whale, Killer Animals Acoustics Vocalization, Animal
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Prediction and interpretation of crash severity using machine learning based on imbalanced traffic crash data.

Journal of safety research Feb 25, 2025
INTRODUCTION: Predicting and interpreting crash severity is essential for developing cost-effective safety measures. Machine learning (ML) models in crash severity studies have attracted much attention recently due to their promising predicted perfor...
Humans Machine Learning Risk Factors Accidents, Traffic Washington
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A machine learning approach to detect potentially harmful and protective suicide-related content in broadcast media.

PloS one May 14, 2024
Suicide-related media content has preventive or harmful effects depending on the specific content. Proactive media screening for suicide prevention is hampered by the scarcity of machine learning approaches to detect specific characteristics in news ...
Suicide Mass Media Washington Oregon Humans Machine Learning Deep Learning Suicide Prevention
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Predicting Outcomes of Antidepressant Treatment in Community Practice Settings.

Psychiatric services (Washington, D.C.) Dec 5, 2023
OBJECTIVE: The authors examined whether machine-learning models could be used to analyze data from electronic health records (EHRs) to predict patients' responses to antidepressant medications.
Humans Machine Learning Electronic Health Records Depressive Disorder Patient Health Questionnaire Washington Community Mental Health Services Male Middle Aged Outcome Assessment, Health Care Antidepressive Agents Female Aged Young Adult Adult
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Using natural language processing to identify child maltreatment in health systems.

Child abuse & neglect Feb 8, 2023
BACKGROUND: Rates of child maltreatment (CM) obtained from electronic health records are much lower than national child welfare prevalence rates indicate. There is a need to understand how CM is documented to improve reporting and surveillance.
Infant, Newborn Infant Adolescent Child, Preschool Humans Electronic Health Records Female Washington Child Natural Language Processing International Classification of Diseases Child Abuse
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Measuring and modelling perceptions of the built environment for epidemiological research using crowd-sourcing and image-based deep learning models.

Journal of exposure science & environmental epidemiology Nov 11, 2022
BACKGROUND: Perceptions of the built environment, such as nature quality, beauty, relaxation, and safety, may be key factors linking the built environment to human health. However, few studies have examined these types of perceptions due to the diffi...
Washington Humans Deep Learning Epidemiologic Studies
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A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization.

JAMA network open Oct 1, 2021
IMPORTANCE: Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response to the pandemic.
Benchmarking COVID-19 Testing Crowdsourcing Washington Clinical Decision Rules Child ROC Curve Models, Statistical Area Under Curve Severity of Illness Index Adolescent Child, Preschool Hospitalization Aged Aged, 80 and over Young Adult Adult Male Middle Aged Algorithms Humans Infant Prognosis Machine Learning Female COVID-19 Infant, Newborn
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Identifying bladder rupture following traumatic pelvic fracture: A machine learning approach.

Injury Dec 9, 2019
INTRODUCTION: Bladder rupture following blunt pelvic trauma is rare though can have significant sequelae. We sought to determine whether machine learning could help predict the presence of bladder injury using certain factors at the time of presentat...
Fractures, Bone Decision Trees Area Under Curve Radiography Bayes Theorem Rupture Urinary Bladder Urinary Bladder Diseases Wounds, Nonpenetrating ROC Curve Logistic Models Pelvic Bones Humans Machine Learning Databases, Factual Retrospective Studies Washington
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Initial report of safety and procedure duration of robotic-assisted chronic total occlusion coronary intervention.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions Sep 4, 2019
BACKGROUND: No previous reports have examined the impact of robotic-assisted (RA) chronic total occlusion (CTO) PCI on procedural duration or safety compared to totally manual CTO PCI.
Male Middle Aged Risk Assessment Time Factors Retrospective Studies Humans Coronary Occlusion Female Patient Safety Treatment Outcome Angioplasty, Balloon, Coronary Risk Factors Robotics Aged Washington Stents Missouri Therapy, Computer-Assisted
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Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.

Pharmacoepidemiology and drug safety Jun 19, 2019
PURPOSE: To enhance automated methods for accurately identifying opioid-related overdoses and classifying types of overdose using electronic health record (EHR) databases.
Datasets as Topic Drug Overdose Self-Injurious Behavior Predictive Value of Tests Heroin Risk Humans Natural Language Processing Electronic Health Records Washington Analgesics, Opioid Sensitivity and Specificity Opioid-Related Disorders
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