Emergency Medicine

Prediction Models in Aneurysmal Subarachnoid Hemorrhage: Forecasting Clinical Outcome With Artificial Intelligence.

BACKGROUND: Predicting outcome after aneurysmal subarachnoid hemorrhage (aSAH) is known to be challenging and complex. Machine learning approaches, of which feedforward artificial neural networks (ffANNs) are the most widely used, could contribute to the patient-specific outcome prediction.

[Effect of rehabilitation robot rehabilitation training synchronizing acupuncture exercise therapy on postoperative rehabilitation with hip fracture].

OBJECTIVE: To compare the therapeutic effect between rehabilitation robot rehabilitation training synchronizing acupuncture exercise therapy and simple acupuncture exercise therapy on lower limb function and life activity ability for postoperative patients with hip fracture.

Towards Equitable AI Interventions for People Who Use Drugs: Key Areas That Require Ethical Investment.

There has been growing investment in artificial intelligence (AI) interventions to combat the opioid-driven overdose epidemic plaguing North America. ...

A Deep Learning Model for Screening Multiple Abnormal Findings in Ophthalmic Ultrasonography (With Video).

PURPOSE: The purpose of this study was to construct a deep learning system for rapidly and accurately screening retinal detachment (RD), vitreous deta...

Enhancing Military Burn- and Trauma-Related Acute Kidney Injury Prediction Through an Automated Machine Learning Platform and Point-of-Care Testing.

CONTEXT.—: Delayed recognition of acute kidney injury (AKI) results in poor outcomes in military and civilian burn-trauma care. Poor predictive abilit...

Emergency department frequent user subgroups: Development of an empirical, theory-grounded definition using population health data and machine learning.

Frequent emergency department (ED) use has been operationalized in research, clinical practice, and policy as number of visits to the ED, despite the ...

[Application of deep learning-based chest CT auxiliary diagnosis system in emergency trauma patients].

To investigate the diagnostic efficacy and potential application value of deep learning-based chest CT auxiliary diagnosis system in emergency trauma...

Advancing care for acute gastrointestinal bleeding using artificial intelligence.

The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision ...

[Lateral Port Site Hernia Following Robot Assisted Laparoscopic Radical Prostatectomy : A Case Report and Literature Review].

The patient was a 69-year-old man with localized cT1cN0M0 prostate cancer, who underwent robotassisted laparoscopic prostatectomy (RALP). The operatio...

[Overview of machine learning and its application in the management of emergency services].

The processes associated with health care generate a large amount of information that is difficult to analyze using standard statistical procedures. I...

Early Detection of Hypotension Using a Multivariate Machine Learning Approach.

INTRODUCTION: The ability to accurately detect hypotension in trauma patients at the earliest possible time is important in improving trauma outcomes....

Decision Support for Tactical Combat Casualty Care Using Machine Learning to Detect Shock.

INTRODUCTION: The emergence of more complex Prolonged Field Care in austere settings and the need to assist inexperienced providers' ability to treat ...

Development of a Complication- and Treatment-Aware Prediction Model for Favorable Functional Outcome in Aneurysmal Subarachnoid Hemorrhage Based on Machine Learning.

BACKGROUND: Current prognostic tools in aneurysmal subarachnoid hemorrhage (aSAH) are constrained by being primarily based on patient and disease char...

Characterizing Opioid Overdoses Using Emergency Medical Services Data : A Case Definition Algorithm Enhanced by Machine Learning.

OBJECTIVES: Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to cr...

Incorporating New Technologies to Overcome the Limitations of Endoscopic Spine Surgery: Navigation, Robotics, and Visualization.

Recently, spine surgery has gradually evolved from conventional open surgery to minimally invasive surgery, and endoscopic spine surgery (ESS) has bec...

AI (artificial intelligence)-assisted planning within emergency management operations.

There is a demand for future technologies to be embedded within emergency management operations. Artificial intelligence (AI) can help save lives and ...

A Simplified Framework for the Detection of Intracranial Hemorrhage in CT Brain Images Using Deep Learning.

BACKGROUND: The need for accurate and timely detection of Intracranial hemorrhage (ICH) is of utmost importance to avoid untoward incidents that may e...

Clinical usefulness of deep learning-based automated segmentation in intracranial hemorrhage.

BACKGROUND: Doctors with various specializations and experience order brain computed tomography (CT) to rule out intracranial hemorrhage (ICH). Advanc...

Seasonal variation in heat shock proteins (hsp70 and hsp90) and their association with frozen semen quality and fertility in buffaloes.

BACKGROUND: Heat shock protein is considered as a potential indicator of animal adaptation to harsh environmental stresses and its expression has been...

End-stage renal disease at dialysis initiation: Epidemiology and mortality risks during the first year of hemodialysis.

Chronic kidney disease (CKD) treated by hemodialysis (HD) is a worldwide major public health problem. Its incidence is getting higher and higher, lead...