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Traffic Injury Prevention Volume 15, 2014 - Issue sup1: Peer-Reviewed Journal for the 58th Annual Scientific Conference of the Association for the Advancement of Automotive Medicine (AAAM), October 2014
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Original Articles

Comparison and Validation of Injury Risk Classifiers for Advanced Automated Crash Notification Systems

Kristofer KusanoVirginia Tech, Blacksburg, VirginiaCorrespondence[email protected]
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Hampton C. GablerVirginia Tech, Blacksburg, VirginiaView further author information
Pages S126-S133 | Received 18 Mar 2014, Accepted 20 May 2014, Published online: 11 Oct 2014

Citations (15)

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Read on this site (2)

Soyoung Jung & Xiao Qin. (2022) Impacts of augmenting heliports with school playgrounds on air medical transport time. Journal of Transportation Safety & Security 14:1, pages 46-66.
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Russell L. Griffin, Shannon Carroll & Jan O. Jansen. (2020) Automatic collision notification availability and emergency response times following vehicle collision—an analysis of the 2017 crash investigation sampling system. Traffic Injury Prevention 21:sup1, pages S135-S139.
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Articles from other publishers (13)

Chenwei Gu, Jinliang Xu, Shuqi Li, Chao Gao & Yongji Ma. (2023) Injury Risk Assessment and Interpretation for Roadway Crashes Based on Pre-Crash Indicators and Machine Learning Methods. Applied Sciences 13:12, pages 6983.
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Joon Seok Kong, Kang Hyun Lee, Oh Hyun Kim, Hee Young Lee, Chan Young Kang, Dooruh Choi, Sang Chul Kim, Hoyeon Jeong, Dae Ryong Kang & Tae-Eung Sung. (2023) Machine learning-based injury severity prediction of level 1 trauma center enrolled patients associated with car-to-car crashes in Korea. Computers in Biology and Medicine 153, pages 106393.
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Michelangelo S. Gulino, Anita Fiorentino & Dario Vangi. (2022) Prospective and retrospective performance assessment of Advanced Driver Assistance Systems in imminent collision scenarios: the CMI-Vr approach. European Transport Research Review 14:1.
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Farshid Afshar, Seyedehsan Seyedabrishami & Sara Moridpour. (2022) Application of Extremely Randomised Trees for exploring influential factors on variant crash severity data. Scientific Reports 12:1.
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Matthew Miller, Duncan Bootland, Louisa Jorm & Blanca Gallego. (2022) Improving ambulance dispatch triage to trauma: A scoping review using the framework of development and evaluation of clinical prediction rules. Injury 53:6, pages 1746-1755.
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Hawzhin Hozhabr Pour, Frédéric Li, Lukas Wegmeth, Christian Trense, Rafał Doniec, Marcin Grzegorzek & Roland Wismüller. (2022) A Machine Learning Framework for Automated Accident Detection Based on Multimodal Sensors in Cars. Sensors 22:10, pages 3634.
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David R. Barnes, Kerry A. Danelson, Nitin M. Moholkar & Kathryn L. Loftis. (2021) Methodology for Evaluation of WIAMan Injury Assessment Reference Curves Using Whole Body Match-Paired Data. Annals of Biomedical Engineering 49:11, pages 3128-3142.
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Stefan Candefjord, Azam Sheikh Muhammad, Pramod Bangalore & Ruben Buendia. (2021) On Scene Injury Severity Prediction (OSISP) machine learning algorithms for motor vehicle crash occupants in US. Journal of Transport & Health 22, pages 101124.
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Michelangelo-Santo Gulino, Leonardo Di Gangi, Alessio Sortino & Dario Vangi. (2021) Injury risk assessment based on pre-crash variables: The role of closing velocity and impact eccentricity. Accident Analysis & Prevention 150, pages 105864.
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Jinlong Qiu, Sen Su, Aowen Duan, Chengjian Feng, Jingru Xie, Kui Li & Zhiyong Yin. (2020) Preliminary injury risk estimation for occupants involved in frontal crashes by combining computer simulations and real crashes. Science Progress 103:2, pages 003685042090875.
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Ang Ji & David Levinson. (2020) Injury Severity Prediction From Two-Vehicle Crash Mechanisms With Machine Learning and Ensemble Models. IEEE Open Journal of Intelligent Transportation Systems 1, pages 217-226.
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Yongbeom Lee, Eungi Cho, Mingyu Park, Hyeonseok Kim, Kyusang Choi & Seongkeun Park. (2018) A Machine Learning Approach to Prediction of Passenger Injuries on Real Road Situation. A Machine Learning Approach to Prediction of Passenger Injuries on Real Road Situation.
Grace Wusk & Hampton Gabler. (2018) Non-Invasive Detection of Respiration and Heart Rate with a Vehicle Seat Sensor. Sensors 18:5, pages 1463.
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