AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Trauma Severity Indices

Showing 11 to 20 of 22 articles

Clear Filters

[Comparison of ICD 10 and AIS with the Development of a Method for Automated Conversion].

Zeitschrift fur Orthopadie und Unfallchirurgie
BACKGROUND: Most of the current scores and outcome prediction calculations in traumatology are based on the Abbreviated Injury Scale (AIS). However, this is not routinely used for documentation and coding of injuries in many countries, including Germ...

Investigating driver injury severity patterns in rollover crashes using support vector machine models.

Accident; analysis and prevention
Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector ...

Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

International journal of injury control and safety promotion
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...

Robot-assisted upper extremity rehabilitation for cervical spinal cord injuries: a systematic scoping review.

Disability and rehabilitation. Assistive technology
UNLABELLED: Abstact Purpose: To provide an overview of the feasibility and outcomes of robotic-assisted upper extremity training for individuals with cervical spinal cord injury (SCI), and to identify gaps in current research and articulate future re...

Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study.

Lancet (London, England)
BACKGROUND: Non-contrast head CT scan is the current standard for initial imaging of patients with head trauma or stroke symptoms. We aimed to develop and validate a set of deep learning algorithms for automated detection of the following key finding...

Using Machine Learning to Identify Change in Surgical Decision Making in Current Use of Damage Control Laparotomy.

Journal of the American College of Surgeons
BACKGROUND: In an earlier study, we reported the successful reduction in the use of damage control laparotomy (DCL); however, no change in the relative frequencies of specific indications was observed. In this study, we aimed to use machine learning ...

The trauma severity model: An ensemble machine learning approach to risk prediction.

Computers in biology and medicine
Statistical theory indicates that a flexible model can attain a lower generalization error than an inflexible model, provided that the setting is appropriate. This is highly relevant for mortality risk prediction with trauma patients, as researchers ...

Comparison of Machine Learning Optimal Classification Trees With the Pediatric Emergency Care Applied Research Network Head Trauma Decision Rules.

JAMA pediatrics
IMPORTANCE: Computed tomographic (CT) scanning is the standard for the rapid diagnosis of intracranial injury, but it is costly and exposes patients to ionizing radiation. The Pediatric Emergency Care Applied Research Network (PECARN) rules for ident...