AI Medical Compendium Topic

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Accidents, Traffic

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The Future of Road Safety: Challenges and Opportunities.

The Milbank quarterly
Policy Points Traditional approaches to addressing motor vehicle crashes are yielding diminishing returns. A comprehensive strategy known as the Safe Systems approach shows promise in both advancing safety and equity and reducing motor vehicle crashe...

Machine learning to predict passenger mortality and hospital length of stay following motor vehicle collision.

Neurosurgical focus
OBJECTIVE: Motor vehicle collisions (MVCs) account for 1.35 million deaths and cost $518 billion US dollars each year worldwide, disproportionately affecting young patients and low-income nations. The ability to successfully anticipate clinical outco...

Application of Deep Learning Methods for Pedestrian Collision Detection Using Dashcam Videos.

Stapp car crash journal
The goal of this study is to clarify the usefulness of deep learning methods for pedestrian collision detection using dashcam videos for advanced automatic collision notification, focusing on pedestrians, as they make up the highest number of traffic...

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

Accident; analysis and prevention
Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual int...

Factors associated with motor vehicle crashes in cognitively impaired older adults.

Alzheimer disease and associated disorders
Because cognitive impairment might pose a safety risk for these drivers and the public, we examined what patient characteristics might be associated with motor vehicle crashes, in a retrospective study of all new referrals to a geriatric clinic speci...