Bayesian Scoring Systems for Military Pelvic and Perineal Blast Injuries: Is it Time to Take a New Approach? | Zendy

Somayyeh Mossadegh | Zendy; Shan He | Zendy; Paul Parker | Zendy

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Bayesian Scoring Systems for Military Pelvic and Perineal Blast Injuries: Is it Time to Take a New Approach?

Author(s) -

Somayyeh Mossadegh,

Shan He,

Paul Parker

Publication year - 2016

Publication title -

military medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.442

H-Index - 67

eISSN - 1930-613X

pISSN - 0026-4075

DOI - 10.7205/milmed-d-15-00171

Subject(s) - medicine , injury severity score , bayesian probability , scoring system , predictive value , military medicine , poison control , injury prevention , computer science , machine learning , artificial intelligence , medical emergency , surgery , political science , law

Various injury severity scores exist for trauma; it is known that they do not correlate accurately to military injuries. A promising anatomical scoring system for blast pelvic and perineal injury led to the development of an improved scoring system using machine-learning techniques.

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