Incidence of post-traumatic seizures in children during combat operations in Afghanistan and Iraq

Artificial intelligence in emergency medicine. A systematic literature review

Motivation and objective: Emergency medicine is becoming a popular application area for artificial intelligence methods but remains less investigated than other healthcare branches. The need for time-sensitive decision-making on the basis of high data volumes makes the use of quantitative technologies inevitable. However, the specifics of healthcare regulations impose strict requirements for such applications. Published contributions cover separate parts of emergency medicine and use disparate data and algorithms. This study aims to systematize the relevant contributions, investigate the main obstacles to artificial intelligence applications in emergency medicine, and propose directions for further studies.

METHODS

The contributions selection process was conducted with systematic electronic databases querying and filtering with respect to established exclusion criteria. Among the 380 papers gathered from IEEE Xplore, ACM Digital Library, Springer Library, ScienceDirect, and Nature databases 116 were considered to be a part of the survey. The main features of the selected papers are the focus on emergency medicine and the use of machine learning or deep learning algorithms.

FINDINGS AND DISCUSSION

The selected papers were classified into two branches: diagnostics-specific and triage-specific. The former ones are focused on either diagnosis prediction or decision support. The latter covers such applications as mortality, outcome, admission prediction, condition severity estimation, and urgent care prediction. The observed contributions are highly specialized within a single disease or medical operation and often use privately collected retrospective data, making them incomparable. These and other issues can be addressed by creating an end-to-end solution based on human-machine interaction.

CONCLUSION

Artificial intelligence applications are finding their place in emergency medicine, while most of the corresponding studies remain isolated and lack higher generalization and more sophisticated methodology, which can be a matter of forthcoming improvements.

Pediatric traumatic brain injuries in war zones: a systematic literature review

Background

Pediatric casualties in war zones are a devastating consequence of armed conflicts, causing significant challenges for affected children, especially in the context of poor access to care. This study aimed to understand traumatic brain injuries (TBIs) in this high-risk population and to identify and provide information for the stakeholders, as well as to recognize severe long-term consequences and develop strategies to prevent them, thus minimizing their burden while aiding in the management of these cases.

Methods

We carried out a systematic literature review following PRISMA guidelines to identify publications discussing traumatic brain injuries in children in the context of war zones, and we analyzed all the collected data.

Results

Our study showed that head injuries were the most common casualty in war zones; male and female children were affected, and the mean age was 8-10 years. Most children were reported to be from Afghanistan, and blasts were the most common mechanism of injury. The mortality fluctuated from 3 to 47%.

Conclusion

There is a lack of evidence-based information regarding the characterization, approach, and management of children with TBI in conflict zones. While the world finds ways to live in peace, there is an urgency to research, train, and deploy enough specialists to these areas, if governments are serious about improving outcomes for this population.