Emergency Medicine

Deep learning versus iterative image reconstruction algorithm for head CT in trauma.

PURPOSE: To compare the image quality between a deep learning-based image reconstruction algorithm (DLIR) and an adaptive statistical iterative reconstruction algorithm (ASiR-V) in noncontrast trauma head CT.

Assessment of the effect of sub-lethal acute toxicity of Emamectin benzoate in using multiple biomarker approach.

Emamectin benzoate (EMB) is a potent neurotoxin agent, widely used for ectoparasites control in aquaculture, but their detailed toxicological implications in are unknown. Thus, this study was conceptualized to determine the LC and to investigate the effects of two sub-lethal concentrations 1/50th of 96 h LC (1.82 μgL) and 1/10thof 96 h LC (9.1 μgL) on hemato-immunological and biochemical response...

Photocatalytic dye degradation and photoexcited anti-microbial activities of green zinc oxide nanoparticles synthesized extracts.

Drug-resistant superbugs (DRS) were isolated from hospital sewage waste and confirmed by a 16S rDNA molecular technique as , , , and . Green nanotechn...

A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation.

BACKGROUND: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for fi...

Rhabdomyolysis: An evidence-based approach.

A 76-year-old lady was found on the floor following a fall at home. She was uninjured, but unable to get up, and had been lying on the floor for rough...

Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances.

We derived machine learning models utilizing features generated by natural language processing (NLP) of free-text data from an ambulance services prov...

Big Data/AI in Neurocritical Care: Maybe/Summary.

Big data (BD) and artificial intelligence (AI) have increasingly been used in neurocritical care. "BD" can be operationally defined as extremely large...

Data Homogeneity Effect in Deep Learning-Based Prediction of Type 1 Diabetic Retinopathy.

This study is aimed at evaluating a deep transfer learning-based model for identifying diabetic retinopathy (DR) that was trained using a dataset with...

Is Blood Loss Greater in Elderly Patients under Antiplatelet or Anticoagulant Medication for Cervical Spine Injury Surgery? A Japanese Multicenter Survey.

INTRODUCTION: In elderly patients with cervical spinal cord injury, comorbidities such as cardiovascular and cerebrovascular diseases are common, with...

A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study.

BACKGROUND: Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a tr...

Robotics, automation, active electrode arrays, and new devices for cochlear implantation: A contemporary review.

In the last two decades, cochlear implant surgery has evolved into a minimally invasive, hearing preservation surgical technique. The devices used dur...

Clinical implications of the newly defined concept of ventilator-associated events in trauma patients.

PURPOSE: Ventilator-associated pneumonia is the most common nosocomial infection in patients with mechanical ventilation. In 2013, the new concept of ...

Application of AI and IoT in Clinical Medicine: Summary and Challenges.

The application of artificial intelligence (AI) technology in the medical field has experienced a long history of development. In turn, some long-stan...

Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence.

Background Missed fractures are a common cause of diagnostic discrepancy between initial radiographic interpretation and the final read by board-certi...

A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.

Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often preclud...

Detecting Distal Radial Fractures from Wrist Radiographs Using a Deep Convolutional Neural Network with an Accuracy Comparable to Hand Orthopedic Surgeons.

In recent years, fracture image diagnosis using a convolutional neural network (CNN) has been reported. The purpose of the present study was to evalua...

Development and validation of a practical machine-learning triage algorithm for the detection of patients in need of critical care in the emergency department.

Identifying critically ill patients is a key challenge in emergency department (ED) triage. Mis-triage errors are still widespread in triage systems a...

Evaluation of a semi-automated data extraction tool for public health literature-based reviews: Dextr.

INTRODUCTION: There has been limited development and uptake of machine-learning methods to automate data extraction for literature-based assessments. ...

Integrated Multiomics Analysis Identifies a Novel Biomarker Associated with Prognosis in Intracerebral Hemorrhage.

Existing treatments for intracerebral hemorrhage (ICH) are unable to satisfactorily prevent development of secondary brain injury after ICH and multip...

Percutaneous Robot-Assisted versus Freehand S Iliosacral Screw Fixation in Unstable Posterior Pelvic Ring Fracture.

OBJECTIVES: To assess the efficiency, safety, and accuracy of S (IS) screw fixation using a robot-assisted method compared with a freehand method.