AIMC Topic: Ohio

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Investigating the influence of socioeconomic factors on the relationships between road characteristics and traffic crash frequency and severity-- A hybrid structural equation modelling - artificial neural networks approach.

Accident; analysis and prevention May 5, 2025
Traffic crashes result from complex interactions between driver, roadway, and environmental factors, which traditional methods often fail to capture. This paper investigates the influence of road, weather, and socioeconomic factors on traffic crashes...
Environment Design Accidents, Traffic Weather Automobile Driving Humans Ohio Neural Networks, Computer Latent Class Analysis Socioeconomic Factors
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Using Natural Language Processing Methods to Predict Topics Included in 2019 Ohio Syphilis Disease Intervention Specialist Records.

Sexually transmitted diseases Feb 11, 2025
BACKGROUND: Free-text notes in disease intervention specialist (DIS) records may contain relevant information for sexual transmitted infection control. In their current form, the notes are not analyzable without manual reading, which is labor-intensi...
Humans Machine Learning Electronic Health Records Natural Language Processing Syphilis Ohio
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Assessing the Potential of a Deep Learning Tool to Improve Fracture Detection by Radiologists and Emergency Physicians on Extremity Radiographs.

Academic radiology Nov 22, 2023
RATIONALE AND OBJECTIVES: To evaluate the standalone performance of a deep learning (DL) based fracture detection tool on extremity radiographs and assess the performance of radiologists and emergency physicians in identifying fractures of the extrem...
Fractures, Bone Radiologists Radiographic Image Interpretation, Computer-Assisted Aged Extremities Aged, 80 and over Ohio Young Adult Adult Sensitivity and Specificity Male Middle Aged Deep Learning Adolescent Child Humans Retrospective Studies Female
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Novel Machine Learning Can Predict Acute Asthma Exacerbation.

Chest Jan 10, 2021
BACKGROUND: Asthma exacerbations result in significant health and economic burden, but are difficult to predict.
Electronic Health Records Female Aged Aged, 80 and over Adult Humans Machine Learning Symptom Flare Up Ohio Asthma Male Middle Aged Adolescent Predictive Value of Tests
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Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.

Circulation. Arrhythmia and electrophysiology Jun 20, 2019
BACKGROUND: Cardiac resynchronization therapy (CRT) has significant nonresponse rates. We assessed whether machine learning (ML) could predict CRT response beyond current guidelines.
Baltimore Progression-Free Survival Practice Guidelines as Topic Heart-Assist Devices Heart Transplantation Aged Ohio Male Predictive Value of Tests Ventricular Function, Left Patient Selection Decision Support Techniques Middle Aged Stroke Volume Heart Failure Humans Retrospective Studies Echocardiography Risk Assessment Cardiac Resynchronization Therapy Machine Learning Disease Progression Clinical Decision-Making Time Factors Female Recovery of Function Risk Factors
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A convolutional route to abbreviation disambiguation in clinical text.

Journal of biomedical informatics Aug 15, 2018
OBJECTIVE: Abbreviations sense disambiguation is a special case of word sense disambiguation. Machine learning methods based on neural networks showed promising results for word sense disambiguation (Festag and Spreckelsen, 2017) [1] and, here we ass...
Algorithms Databases, Factual Language Reproducibility of Results Hospitals Deep Learning Support Vector Machine Cluster Analysis Data Collection Medical Informatics Neural Networks, Computer Software Automation Semantics Ohio
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Risks and Benefits of Pharmacological Prophylaxis for Venous Thromboembolism Prevention in Patients Undergoing Robotic Partial Nephrectomy.

The Journal of urology Nov 26, 2015
PURPOSE: We investigate the safety and efficacy of pharmacological venous thromboembolism prophylaxis in patients treated with robotic partial nephrectomy at our center.
Retrospective Studies Robotics Female Anticoagulants Postoperative Complications Humans Male Venous Thromboembolism Incidence Middle Aged Nephrectomy Treatment Outcome Risk Assessment Ohio Follow-Up Studies Operative Time
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Comparison of UMLS terminologies to identify risk of heart disease using clinical notes.

Journal of biomedical informatics Sep 12, 2015
The second track of the 2014 i2b2 challenge asked participants to automatically identify risk factors for heart disease among diabetic patients using natural language processing techniques for clinical notes. This paper describes a rule-based system ...
Computer Security Vocabulary, Controlled Diabetes Complications Ohio Cohort Studies Male Humans Confidentiality Longitudinal Studies Middle Aged Electronic Health Records Data Mining Narration Risk Assessment Female Pattern Recognition, Automated Natural Language Processing Comorbidity Aged Terminology as Topic Coronary Artery Disease Incidence Unified Medical Language System
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Using applied machine learning to predict healthcare utilization based on socioeconomic determinants of care.

The American journal of managed care Jan 1, 2020
OBJECTIVES: To determine if it is possible to risk-stratify avoidable utilization without clinical data and with limited patient-level data.
Decision Trees Emergency Service, Hospital Social Determinants of Health Risk Georgia Infant Adolescent Child, Preschool Child Socioeconomic Factors Patient Acceptance of Health Care Ohio Alabama Humans Machine Learning Female Hospitalization Aged Young Adult Adult Male Middle Aged
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Radiology and Enterprise Medical Imaging Extensions (REMIX).

Journal of digital imaging Feb 1, 2018
Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner M...
Radiology Radiology Information Systems Ohio Humans Artificial Intelligence Neoplasms Image Processing, Computer-Assisted
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