Identification of the motor vehicle accident victim who abuses alcohol: an opportunity to reduce trauma.

1996 ◽  
Vol 57 (6) ◽  
pp. 652-658 ◽  
Author(s):  
M Mancino ◽  
M R Cunningham ◽  
P Davidson ◽  
R L Fulton
Keyword(s):  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Vehicle Accident ◽  
Accident Victim

scholarly journals Increased atlanto-dental interval in a motor vehicle accident victim

Injury Extra ◽  
2008 ◽  
Vol 39 (1) ◽  
pp. 1-3 ◽  
Author(s):  
Hermione Race ◽  
Damian Balmforth ◽  
Arjan B. Van As
Keyword(s):  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Vehicle Accident ◽  
Accident Victim

scholarly journals Life After Surviving Vehicular Accident: A Phenomenological Inquiry

2020 ◽  
Vol 4 (11) ◽  
pp. 364-368
Author(s):  
Edmelyn B. Cacayan ◽  
Shayne R. Babaran ◽  
Romella Mendez Tuppal
Keyword(s):  
Sleep Disturbances ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Phenomenological Inquiry ◽  
Face To Face ◽  
Vehicle Accidents ◽  
Vehicle Accident ◽  
Accident Victim ◽  
Psychological Assistance ◽  
Qualitative Phenomenological

Worldwide, one of the leading causes of death and injuries are motor vehicle accidents. This study was conducted to explore motor vehicle accident victims’ experiences after vehicular accident in an attempt to further understand the phenomenon. It is important to know the effects of the accident to the life of survivors in order to make a specific intervention to their specific needs. A qualitative phenomenological design is used, using semi-structured, in depth face to face interviews to elicit accounts of vehicular accident survivors. Findings revealed that driving under influence of alcohol, over speeding, slippery road, and first time driving are some of the causes of accident. Five of the respondents had experienced disturbing thoughts, and some of them had dreams of the accident were happening again. Six of the respondents were afraid that it will happen again when something or someone reminded them of the accident or when seeing the place where they experienced the accident. The result of this study will help and assist health professionals in developing a plan of care to victims of vehicular accidents regardless of severity to have psychological assistance to avoid future problems such as recurrent thoughts, sleep disturbances and others. Keyword: vehicular accident; victim

scholarly journals Traumatic Pneumorrhachis in a Young Male Motor Vehicle Accident Victim

2016 ◽  
Vol 2 (7) ◽  
pp. 49-54
Author(s):  
Hamid Behzadnia ◽  
Babak Alijani ◽  
Armin Ramzannezhad ◽  
Siavash Dehghani ◽  
◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Young Male ◽  
Vehicle Accident ◽  
Accident Victim

Virtual reality and computer games in the treatment of driving phobia induced by a motor vehicle accident

2003 ◽  
Author(s):  
David Walshe ◽  
Elizabeth Lewis ◽  
Kathleen O'Sullivan ◽  
Brenda K. Wiederhold ◽  
Sun I. Kim
Keyword(s):  
Virtual Reality ◽  
Computer Games ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Vehicle Accident

Machine Learning of Motor Vehicle Accident Categories from Narrative Data

1996 ◽  
Vol 35 (04/05) ◽  
pp. 309-316 ◽  
Author(s):  
M. R. Lehto ◽  
G. S. Sorock
Keyword(s):  
Machine Learning ◽  
Bayesian Model ◽  
Keyword Search ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Computer Search ◽  
Vehicle Accident ◽  
Learning Technique ◽  
Expert Ratings ◽  
Keyword Searches

Abstract:Bayesian inferencing as a machine learning technique was evaluated for identifying pre-crash activity and crash type from accident narratives describing 3,686 motor vehicle crashes. It was hypothesized that a Bayesian model could learn from a computer search for 63 keywords related to accident categories. Learning was described in terms of the ability to accurately classify previously unclassifiable narratives not containing the original keywords. When narratives contained keywords, the results obtained using both the Bayesian model and keyword search corresponded closely to expert ratings (P(detection)≥0.9, and P(false positive)≤0.05). For narratives not containing keywords, when the threshold used by the Bayesian model was varied between p>0.5 and p>0.9, the overall probability of detecting a category assigned by the expert varied between 67% and 12%. False positives correspondingly varied between 32% and 3%. These latter results demonstrated that the Bayesian system learned from the results of the keyword searches.

Aspirated teeth - rigid or flexible bronchoscopy

2019 ◽  
pp. 1-2
Keyword(s):  
Clinical Practice ◽  
Foreign Bodies ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Flexible Bronchoscopy ◽  
Vehicle Accident

Tracheobronchial foreign bodies are a common problem in clinical practice. We present the case of a patient with three aspirated teeth following a motor vehicle accident.

Isolated second trimester uterine rupture following a motor vehicle accident

2021 ◽  
Vol 258 ◽  
pp. 461-463
Author(s):  
Tal Margaliot Kalifa ◽  
Misgav Rottenstreich ◽  
Eyal Mazaki ◽  
Hen Y. Sela ◽  
Schwartz Alon ◽  
...  
Keyword(s):  
Uterine Rupture ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Second Trimester ◽  
Vehicle Accident
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