Emergency Medicine

Advanced medical monitoring for the battlefield: A review on clinical applicability of compensatory reserve measurements for early and accurate hemorrhage detection.

Hemorrhagic shock remains the leading cause of mortality in civilian trauma and battlefield settings. The ability of combat medics and other military medical personnel to obtain early identification and assessment of a bleeding casualty is hampered by the use of standard vital signs that fail to provide early predictive indicators of the onset of shock because of compensatory mechanisms. Over the ...

A deep learning framework for automated detection and quantitative assessment of liver trauma.

BACKGROUND: Both early detection and severity assessment of liver trauma are critical for optimal triage and management of trauma patients. Current trauma protocols utilize computed tomography (CT) assessment of injuries in a subjective and qualitative (v.s. quantitative) fashion, shortcomings which could both be addressed by automated computer-aided systems that are capable of generating real-tim...

Hematoma Expansion Context Guided Intracranial Hemorrhage Segmentation and Uncertainty Estimation.

Accurate segmentation of the Intracranial Hemorrhage (ICH) in non-contrast CT images is significant for computer-aided diagnosis. Although existing me...

Development of Machine Learning-Based Predictor Algorithm for Conversion of an Ommaya Reservoir to a Permanent Cerebrospinal Fluid Shunt in Preterm Posthemorrhagic Hydrocephalus.

BACKGROUND: An Ommaya reservoir can be used to treat posthemorrhagic hydrocephalus secondary to intraventricular hemorrhage of prematurity until an ac...

Update on risk factors and biomarkers of sudden unexplained cardiac death.

Sudden cardiac death (SCD) accounts for approximately 15%-20% of all deaths worldwide, the causes of which are mainly structural heart diseases. Howev...

Deep Learning to Predict Traumatic Brain Injury Outcomes in the Low-Resource Setting.

OBJECTIVE: Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these settings, accurate patient progn...

Building artificial intelligence and machine learning models : a primer for emergency physicians.

There has been a rise in the number of studies relating to the role of artificial intelligence (AI) in healthcare. Its potential in Emergency Medicine...

Postsurgical complications after robot-assisted transaxillary thyroidectomy: critical analysis of a large cohort of European patients.

In the last decade, robot-assisted trans-axillary thyroidectomy has spread rapidly and has been proven to be a safe and effective procedure. However, ...

Human-robot-robot cooperative control using positioning robot and 1-DOF traction device for robot-assisted fracture reduction system.

While performing musculoskeletal long bone fracture reduction surgery, assistant surgeons can often suffer from physical fatigue as they provide resis...

A robotic magnetic resonance-guided high-intensity focused ultrasound platform for neonatal neurosurgery: Assessment of targeting accuracy and precision in a brain phantom.

BACKGROUND: Intraventricular hemorrhage (IVH) is one of the most serious neurovascular complications resulting from premature birth. It can result in ...

Comparison of Pericapsular Nerve Group Block versus Fascia Iliaca Compartment Block as Postoperative Pain Management in Hip Fracture Surgeries.

BACKGROUND AND OBJECTIVES: Postoperative pain management and early recovery play an important role in the functional outcome following hip surgeries. ...

[Clinical value of alternative technologies to standard laparoscopic cholecystectomy - single port, reduced port, robotics, NOTES].

Surgical interventions should ideally treat an existing disease curatively and achieve this with a low complication rate and minimal trauma. In this s...

Advances in computed tomography-based prognostic methods for intracerebral hemorrhage.

Spontaneous intracerebral hemorrhage (ICH) has high morbidity and mortality. Computed tomography (CT) plays an important role in the diagnosis, treatm...

Detection of Backdoors in Trained Classifiers Without Access to the Training Set.

With wide deployment of deep neural network (DNN) classifiers, there is great potential for harm from adversarial learning attacks. Recently, a specia...

Contingency response decision of network public opinion emergencies based on intuitionistic fuzzy entropy and preference information of decision makers.

A multi-attribute group decision-making (MAGDM) method based on intuitionistic fuzzy preference information is proposed for the multi-attribute intuit...

Application of Esmolol to Control Heart Rate and Artificial Intelligence Reconstruction Analysis for Rapid Zero-Cooperation Emergency Coronary CTA.

OBJECTIVE: To investigate a rapid and effective method for the examination of coronary CTA in emergency patients requiring coronary CTA examination, w...

LDIAED: A lightweight deep learning algorithm implementable on automated external defibrillators.

Differentiating between shockable and non-shockable Electrocardiogram (ECG) signals would increase the success of resuscitation by the Automated Exter...

Can Artificial Intelligence Be Applied to Diagnose Intracerebral Hemorrhage under the Background of the Fourth Industrial Revolution? A Novel Systemic Review and Meta-Analysis.

AIM: We intended to provide the clinical evidence that artificial intelligence (AI) could be used to assist doctors in the diagnosis of intracerebral ...

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction.

This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multisca...

Deep learning identifies Acute Promyelocytic Leukemia in bone marrow smears.

BACKGROUND: Acute promyelocytic leukemia (APL) is considered a hematologic emergency due to high risk of bleeding and fatal hemorrhages being a major ...