AIMC Topic: Prospective Studies
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Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.
BMC pregnancy and childbirth
Feb 23, 2024
BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CU...
Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM).
European radiology
Feb 22, 2024
PURPOSE: Frequent CT scans to quantify lung involvement in cystic lung disease increases radiation exposure. Beam shaping energy filters can optimize imaging properties at lower radiation dosages. The aim of this study is to investigate whether use o...
Improved 3D DESS MR neurography of the lumbosacral plexus with deep learning and geometric image combination reconstruction.
Skeletal radiology
Feb 22, 2024
OBJECTIVE: To evaluate the impact of deep learning (DL) reconstruction in enhancing image quality and nerve conspicuity in LSP MRN using DESS sequences. Additionally, a geometric image combination (GIC) method to improve DESS signals' combination was...
Analysis of robot-specific operative time and surgical team anxiety level and its effect on alignment during robot-assisted TKA.
Journal of robotic surgery
Feb 22, 2024
Adapting to robotic-assisted (RA) total knee arthroplasty (TKA) is hindered by the surgeon's fear of extra time. The main purpose of this study was to determine the robot's operative time, and the secondary goals were to assess the surgical team's an...
Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT.
PloS one
Feb 22, 2024
PURPOSE: To prospectively evaluate whether Lung-RADS classification and volumetric nodule assessment were feasible with ultralow-dose (ULD) chest CT scans with deep learning image reconstruction (DLIR).
Improving Access to Eye Care Through Community Health Screenings Using Artificial Intelligence.
Ophthalmic epidemiology
Feb 21, 2024
PURPOSE: To the best of our knowledge, implementation of artificial intelligence (AI)-based vision screening in community health fair settings has not been previously studied. This prospective cohort study explored the incorporation of AI in a commun...
Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial.
Critical care medicine
Feb 21, 2024
OBJECTIVES: Machine learning algorithms can outperform older methods in predicting clinical deterioration, but rigorous prospective data on their real-world efficacy are limited. We hypothesized that real-time machine learning generated alerts sent d...
Initial Experience in Urological Surgery with a Novel Robotic Technology: Magnetic-Assisted Robotic Surgery in Urology.
Journal of endourology
Feb 20, 2024
Magnetic-assisted robotic surgery (MARS) has been developed to maximize patient benefits of minimally invasive surgery while enhancing surgeon control and visualization. MARS platform (Levita Magnetics) comprises two robotic arms that provide contro...
Diagnostic Performance of Deep Learning in Video-Based Ultrasonography for Breast Cancer: A Retrospective Multicentre Study.
Ultrasound in medicine & biology
Feb 17, 2024
OBJECTIVE: Although ultrasound is a common tool for breast cancer screening, its accuracy is often operator-dependent. In this study, we proposed a new automated deep-learning framework that extracts video-based ultrasound data for breast cancer scre...
Automated Real-Time Detection of Lung Sliding Using Artificial Intelligence: A Prospective Diagnostic Accuracy Study.
Chest
Feb 15, 2024
BACKGROUND: Rapid evaluation for pneumothorax is a common clinical priority. Although lung ultrasound (LUS) often is used to assess for pneumothorax, its diagnostic accuracy varies based on patient and provider factors. To enhance the performance of ...
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