Enhancing Radiologist Efficiency with AI: A Multi-Reader Multi-Case Study on Aortic Dissection Detection and Prioritization.

Background And Objectives: Acute aortic dissection (AD) is a life-threatening condition in which early detection can significantly improve patient outcomes and survival. This study evaluates the clinical benefits of integrating a deep learning (DL)-based application for the automated detection and prioritization of AD on chest CT angiographies (CTAs) with a focus on the reduction in the scan-to-assessment time (STAT) and interpretation time (IT).

Materials And Methods: This retrospective Multi-Reader Multi-Case (MRMC) study compared AD detection with and without artificial intelligence (AI) assistance.

Effects of Creatine Supplementation on the Performance, Physiological Response, and Body Composition Among Swimmers: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: Although recent studies have increasingly focused on examining the potential benefits of creatine supplementation to improve performance in swimming events, the impact of creatine supplementation on swimming performance remains a topic of debate and controversy. A comprehensive meta-analytical review was undertaken to evaluate the effects of creatine supplementation on the performance, physiological response, and body composition among swimmers.

Methods: The research methodology adhered strictly to the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

Building and testing of a robotic intervention framework to enhancing the social engagement of children with autism spectrum disorder.

Purpose: Humanoid robot intervention programmes for children with autism spectrum disorder (ASD) are being developed rapidly. This study aimed to develop and test a robotic intervention framework for children with ASD to ensure best practice.

Methods: In Phase I of this study, an initial framework was built based on a scoping review.

Differences in the stride time and lower limb joint angles and their variability during distance running between treadmill and over-ground: a crossover study.

Background: Treadmills have been used in laboratories to assess various measures related to walking and running. However, there has been some skepticism regarding their reliability as a representation of outdoor running. While marathon running has gained popularity as a form of physical activity, there have been few studies examining stride-to-stride variability after distance running, especially in relation to the duration and surface of running.

Diagnostic Performance of a Deep Learning-Powered Application for Aortic Dissection Triage Prioritization and Classification.

This multicenter retrospective study evaluated the diagnostic performance of a deep learning (DL)-based application for detecting, classifying, and highlighting suspected aortic dissections (ADs) on chest and thoraco-abdominal CT angiography (CTA) scans. CTA scans from over 200 U.S.

Generating colloquial radiology reports with large language models.

Objectives: Patients are increasingly being given direct access to their medical records. However, radiology reports are written for clinicians and typically contain medical jargon, which can be confusing. One solution is for radiologists to provide a "colloquial" version that is accessible to the layperson.

Performance and clinical utility of an artificial intelligence-enabled tool for pulmonary embolism detection.

Purpose: Diagnosing pulmonary embolism (PE) is still challenging due to other conditions that can mimic its appearance, leading to incomplete or delayed management and several inter-observer variabilities. This study evaluated the performance and clinical utility of an artificial intelligence (AI)-based application designed to assist clinicians in the detection of PE on CT pulmonary angiography (CTPA).

Patients And Methods: CTPAs from 230 US cities acquired on 57 scanner models from 6 different vendors were retrospectively collected.

Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial.

Background And Purpose: Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been well-studied. This study investigates the impact of artificial intelligence assistance on the diagnostic accuracy for intracranial hemorrhage and large-vessel occlusion by medical students and resident trainees.

Comparison of muscle activity in school students while carrying backpacks and trolley bags.

Background: Trolley bags have gained popularity among students, but there is limited research comparing them to backpack-style school bags.

Objective: This study aimed to compare how carrying a backpack versus a trolley bag affects the activity of trunk and lower limb muscles in secondary school students.

Methods: Electromyographic activity was measured in 25 students (13.

Effectiveness of Robotic Intervention on Improving Social Development and Participation of Children with Autism Spectrum Disorder - A Randomised Controlled Trial.

Evidence-based robotic intervention programmes for children with autism spectrum disorder (ASD) have been limited. As yet, there is insufficient evidence to inform therapists, teachers, and service providers on effectiveness of robotic intervention to enhance social development and participation of children with ASD in a real context. This study used a randomised controlled trial to test the efficacy of robotic intervention programmes in enhancing the social development and participation of children with ASD.

Tracking Bilateral Lower Limb Kinematics of Distance Runners on Treadmill Using a Single Inertial Measurement Unit.

Distance running related injuries are common, and many ailments have been associated with faulty posture. Conventional measurement of running kinematics requires sophisticated motion capture system in laboratory. In this study, we developed a wearable solution to accurately predict lower limb running kinematics using a single inertial measurement unit placed on the left lower leg.

Posttreatment Surveillance Imaging After Radiation for Head and Neck Cancer.

Importance: The role of surveillance imaging after treatment for head and neck cancer is controversial and evidence to support decision-making is limited.

Objective: To determine the use of surveillance imaging in asymptomatic patients with head and neck cancer in remission after completion of chemoradiation.

Design, Setting, And Participants: This was a retrospective, comparative effectiveness research review of adult patients who had achieved a complete metabolic response to initial treatment for head and neck cancer as defined by having an unequivocally negative positron emission tomography (PET) scan using the PET response criteria in solid tumors (PERCIST) scale within the first 6 months of completing therapy.

Current role of portable MRI in diagnosis of acute neurological conditions.

Neuroimaging is an inevitable component of the assessment of neurological emergencies. Magnetic resonance imaging (MRI) is the preferred imaging modality for detecting neurological pathologies and provides higher sensitivity than other modalities. However, difficulties such as intra-hospital transport, long exam times, and availability in strict access-controlled suites limit its utility in emergency departments and intensive care units (ICUs).

Influence of Lateral Sitting Wedges on the Rasterstereographically Measured Scoliosis Angle in Patients Aged 10-18 Years with Adolescent Idiopathic Scoliosis.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional axial deviation of the spine diagnosed in adolescence. Despite a long daily sitting duration, there are no studies on whether scoliosis can be positively influenced by sitting on a seat wedge. For the prospective study, 99 patients with AIS were measured with the DIERS formetric III 4D average, in a standing position, on a level seat and with three differently inclined seat wedges (3°, 6° and 9°).

Fitting a stochastic model of intensive care occupancy to noisy hospitalization time series during the COVID-19 pandemic.

Intensive care occupancy is an important indicator of health care stress that has been used to guide policy decisions during the COVID-19 pandemic. Toward reliable decision-making as a pandemic progresses, estimating the rates at which patients are admitted to and discharged from hospitals and intensive care units (ICUs) is crucial. Since individual-level hospital data are rarely available to modelers in each geographic locality of interest, it is important to develop tools for inferring these rates from publicly available daily numbers of hospital and ICU beds occupied.

Exergaming and education: a relational model for games selection and evaluation.

Exergaming, or technology-driven physical exercise, has gained popularity in recent years. Its applications include physical education, health promotion, and rehabilitation. Although studies have obtained promising results regarding the positive effects of exergaming, the outcomes of exergaming for different populations remain undetermined.

Impact of an automated large vessel occlusion detection tool on clinical workflow and patient outcomes.

Purpose: Automated large vessel occlusion (LVO) tools allow for prompt identification of positive LVO cases, but little is known about their role in acute stroke triage when implemented in a real-world setting. The purpose of this study was to evaluate the automated LVO detection tool's impact on acute stroke workflow and clinical outcomes.

Materials And Methods: Consecutive patients with a computed tomography angiography (CTA) presenting with suspected acute ischemic stroke were compared before and after the implementation of an AI tool, RAPID LVO (RAPID 4.

Methamphetamine use increases the risk of cerebral small vessel disease in young patients with acute ischemic stroke.

Methamphetamine use causes spikes in blood pressure. Chronic hypertension is a major risk factor for cerebral small vessel disease (cSVD). The aim of this study is to investigate whether methamphetamine use increases the risk of cSVD.

Neutralizing Monoclonal Antibody Use and COVID-19 Infection Outcomes.

Importance: Evidence on the effectiveness and safety of COVID-19 therapies across a diverse population with varied risk factors is needed to inform clinical practice.

Objective: To assess the safety of neutralizing monoclonal antibodies (nMAbs) for the treatment of COVID-19 and their association with adverse outcomes.

Design, Setting, And Participants: This retrospective cohort study included 167 183 patients from a consortium of 4 health care systems based in California, Minnesota, Texas, and Utah.

Deep Learning-Based Algorithm for Automatic Detection of Pulmonary Embolism in Chest CT Angiograms.

Purpose: Since the prompt recognition of acute pulmonary embolism (PE) and the immediate initiation of treatment can significantly reduce the risk of death, we developed a deep learning (DL)-based application aimed to automatically detect PEs on chest computed tomography angiograms (CTAs) and alert radiologists for an urgent interpretation. Convolutional neural networks (CNNs) were used to design the application. The associated algorithm used a hybrid 3D/2D UNet topology.

Head-to-head comparison of commercial artificial intelligence solutions for detection of large vessel occlusion at a comprehensive stroke center.

Purpose: Despite the availability of commercial artificial intelligence (AI) tools for large vessel occlusion (LVO) detection, there is paucity of data comparing traditional machine learning and deep learning solutions in a real-world setting. The purpose of this study is to compare and validate the performance of two AI-based tools (RAPID LVO and CINA LVO) for LVO detection.

Materials And Methods: This was a retrospective, single center study performed at a comprehensive stroke center from December 2020 to June 2021.