Real-time breath recognition by movies from a small drone landing on victim's bodies

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.

Grasping extreme aerodynamics on a low-dimensional manifold

Modern air vehicles perform a wide range of operations, including transportation, defense, surveillance, and rescue. These aircraft can fly in calm conditions but avoid operations in gusty environments, encountered in urban canyons, over mountainous terrains, and in ship wakes. With extreme weather becoming ever more frequent due to global warming, it is anticipated that aircraft, especially those that are smaller in size, will encounter sizeable atmospheric disturbances and still be expected to achieve stable flight. However, there exists virtually no theoretical fluid-dynamic foundation to describe the influence of extreme vortical gusts on wings. To compound this difficulty, there is a large parameter space for gust-wing interactions. While such interactions are seemingly complex and different for each combination of gust parameters, we show that the fundamental physics behind extreme aerodynamics is far simpler and lower-rank than traditionally expected. We reveal that the nonlinear vortical flow field over time and parameter space can be compressed to only three variables with a lift-augmented autoencoder while holding the essence of the original high-dimensional physics. Extreme aerodynamic flows can be compressed through machine learning into a low-dimensional manifold, which can enable real-time sparse reconstruction, dynamical modeling, and control of extremely unsteady gusty flows. The present findings offer support for the stable flight of next-generation small air vehicles in atmosphere conditions traditionally considered unflyable.

The Intersection of Telemedicine and Wilderness Care: Past, Present, and Future

Wilderness medicine and telemedicine seemingly exist at opposite ends of the clinical continuum. However, these 2 specialties share a common history and the literature abounds with examples of successful deployment of telemedicine to resource limited settings. The recent widespread adoption of telemedicine has important ramifications for wilderness providers. Telemedicine is inherently reliant on some sort of technology. There is a wide spectrum of complexity involved, but in general these systems rely on a hardware component, a software component, and a network system to transmit information from place to place. Today, connectivity is nearly ubiquitous through access to cellular networks, Wi-Fi, or communication satellites. However, bandwidth, defined as the amount of data which can be transmitted through a given connection over time, remains a limiting factor for many austere settings. Telemedicine services are typically organized into 4 categories: 1) live/interactive; 2) store and forward; 3) remote patient monitoring; and 4) mHealth. Each of these categories has an applicable wilderness medicine use case which will be reviewed in this paper. Though the regulatory environment remains complex, there is enormous potential for telemedicine to enhance the practice of wilderness medicine. Drones are likely to transform wilderness medicine supply chains by facilitating delivery of food, shelter, and medicines and are able to enhance search and rescue efforts. Remote consultations can be paired with remote patient monitoring technology to deliver highly specialized care to austere environments. Early feasibility studies are promising, but further prospective data will be required to define future best practices for wilderness telemedicine.

Development of the Use of Unmanned Aerial Vehicles (UAVs) in Emergency Rescue in China

With the frequent occurrence of various disaster events, China has attached high importance to emergency rescue in recent years. Unmanned aerial vehicles (UAVs) are becoming more extensively used in emergency rescue, thanks to their flexibility, intellectuality, and safety in operation. It is therefore timely to evaluate UAV utilization in emergency rescue and explore the impediments to its further development in China. To date, UAVs have been mainly used for on-site monitoring and commanding, relay of communications, delivery of materials, disaster assessment, and life detection. Aerial emergency rescue is a vital component of the whole emergency rescue system in China. In the future, it is recommended that China take measures to boost UAV technical innovation and professional team development and promote the integrated application of manned aircraft and UAVs.

Development of the Aerial Remote Triage System using drones in mass casualty scenarios: A survey of international experts

The use of drones for triage in mass-casualty incidents has recently emerged as a promising technology. However, there is no triage system specifically adapted to a remote usage. Our study aimed to develop a remote triage procedure using drones. The research was performed in three stages: literature review, the development of a remote triage algorithm using drones and evaluation of the algorithm by experts. Qualitative synthesis and the calculation of content validity ratios were done to achieve the Aerial Remote Triage System. This algorithm assesses (in this order): major bleeding, walking, consciousness and signs of life; and then classify the injured people into several priority categories: priority 1 (red), priority 2 (yellow), priority 3 (green) and priority * (violet). It includes the possibility to indicate save-living interventions to injured people and bystanders, like the compression of bleeding injuries or the adoption of the recovery position. The Aerial Remote Triage System may be a useful way to perform triage by drone in complex emergencies when it is difficult to access to the scene due to physical, chemical or biological risks.