Emergency Medicine

Transportability and Implementation Challenges of Early Warning Scores for Septic Shock in the ICU: A Perspective on the TREWScore.

The increased use of electronic health records (EHRs) has improved the availability of routine care data for medical research. Combined with machine learning techniques this has spurred the development of early warning scores (EWSs) in hospitals worldwide. EWSs are commonly used in the hospital where they have been developed, yet few have been transported to external settings and/or internationall...

Artificial Intelligence Technology-Based Medical Information Processing and Emergency First Aid Nursing Management.

This study was aimed at exploring the new management mode of medical information processing and emergency first aid nursing management under the new artificial intelligence technology. This study will use the artificial intelligence algorithm to optimize medical information processing and emergency first aid nursing management process, in order to improve the efficiency of emergency department and...

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the Res...

Exploring the use of machine learning for the assessment of skeletal fracture morphology and differentiation between impact mechanisms: A pilot study.

Analyzing and interpreting traumatic injuries is a fundamental aspect of routine forensic case work. As the human skeleton can be impacted through a c...

Potential Application of Machine-Learning-Based Quantum Chemical Methods in Environmental Chemistry.

It is an important topic in environmental sciences to understand the behavior and toxicology of chemical pollutants. Quantum chemical methodologies ha...

An Experimental Safety Response Mechanism for an Autonomous Moving Robot in a Smart Manufacturing Environment Using Q-Learning Algorithm and Speech Recognition.

The industrial manufacturing sector is undergoing a tremendous revolution moving from traditional production processes to intelligent techniques. Unde...

Articulation is essential: First in cardiovascular surgery implementation of 360° surgeon-powered robotic instruments.

Since the development of endoscopic vision in the late 1970s, the implementation of minimally invasive surgical methods has been rapidly progressing t...

Development and validation of a machine learning method to predict intraoperative red blood cell transfusions in cardiothoracic surgery.

Accurately predicting red blood cell (RBC) transfusion requirements in cardiothoracic (CT) surgery could improve blood inventory management and be use...

Artificial Intelligence-Based Smart Comrade Robot for Elders Healthcare with Strait Rescue System.

A rising proportion of older people has more demand on services including hospitals, retirement homes, and assisted living facilities. Regaining contr...

Assessment of germinal matrix hemorrhage on head ultrasound with deep learning algorithms.

BACKGROUND: Germinal matrix hemorrhage-intraventricular hemorrhage is among the most common intracranial complications in premature infants. Early det...

Robotic surgery in emergency setting: 2021 WSES position paper.

BACKGROUND: Robotics represents the most technologically advanced approach in minimally invasive surgery (MIS). Its application in general surgery has...

Machine learning prediction model of acute kidney injury after percutaneous coronary intervention.

Acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a significant risk of morbidity and mortality. The traditi...

Comparison of ARIMA and LSTM for prediction of hemorrhagic fever at different time scales in China.

OBJECTIVES: This study intends to build and compare two kinds of forecasting models at different time scales for hemorrhagic fever incidence in China.

Using the Social Robot NAO for Emotional Support to Children at a Pediatric Emergency Department: Randomized Clinical Trial.

BACKGROUND: Social robots (SRs) have been used for improving anxiety in children in stressful clinical situations, such as during painful procedures. ...

Application of machine learning missing data imputation techniques in clinical decision making: taking the discharge assessment of patients with spontaneous supratentorial intracerebral hemorrhage as an example.

BACKGROUND: There are often many missing values in medical data, which directly affect the accuracy of clinical decision making. Discharge assessment ...

Machine learning algorithms as new screening approach for patients with endometriosis.

Endometriosis-a systemic and chronic condition occurring in women of childbearing age-is a highly enigmatic disease with unresolved questions. While m...

A Study on 3D Deep Learning-Based Automatic Diagnosis of Nasal Fractures.

This paper reported a study on the 3-dimensional deep-learning-based automatic diagnosis of nasal fractures. (1) Background: The nasal bone is the mos...

Constraint of musculoskeletal tissue and path planning of robot-assisted fracture reduction with collision avoidance.

BACKGROUND: For the robot-assisted fracture reduction, due to the complex fracture musculoskeletal environment, it is necessary to consider the influe...

Insurance payment for artificial intelligence technology: Methods used by a stroke artificial intelligence system and strategies to qualify for the new technology add-on payment.

The first ever insurance reimbursement for an artificial intelligence (AI) system, which expedites triage of acute stroke, occurred in 2020 when the C...

FDA-approved deep learning software application versus radiologists with different levels of expertise: detection of intracranial hemorrhage in a retrospective single-center study.

PURPOSE: To assess an FDA-approved and CE-certified deep learning (DL) software application compared to the performance of human radiologists in detec...