INTRODUCTION: Many studies display significant heterogeneity in the reliability of artificial intelligence (AI) assessment of minimally invasive surgical (MIS) skills. Our objective is to investigate whether AI systems utilising standardised objectiv...
PURPOSE: The aim of this study was to systematically review the use of automated detection systems for identifying bone lesions based on CT and MRI, focusing on advancements in artificial intelligence (AI) applications.
Autonomous laboratories can accelerate discoveries in chemical synthesis, but this requires automated measurements coupled with reliable decision-making. Most autonomous laboratories involve bespoke automated equipment, and reaction outcomes are ofte...
Journal of magnetic resonance imaging : JMRI
Nov 5, 2024
BACKGROUND: Tubular microdiscectomy (TMD) is a treatment for lumbar disc herniation (LDH). Although the combination of MRI and deep learning (DL) has shown promise, its application in evaluating postoperative outcomes in TMD has not been fully explor...
OBJECTIVE: To estimate proton density fat fraction (PDFF) from chemical shift encoded (CSE) MR images using a deep learning (DL)-based method that is precise and robust to different MR scanners and acquisition echo times (TEs).
OBJECTIVES: To date, AI-supported programs for bone age (BA) determination for medical use in Europe have almost only been validated separately, according to Greulich and Pyle (G&P). Therefore, the current study aimed to compare the performance of th...
PURPOSE: ChatGPT is a widely used artificial intelligence modeling tool. Healthcare is one potential area of use of ChatGPT. This study aimed to test the usability and reliability of ChatGPT in acromegaly, which is less known in society and should be...
Research in social & administrative pharmacy : RSAP
Nov 5, 2024
BACKGROUND: Pharmacy practice faculty research profiles extend beyond the clinical and social domains, which are core elements of pharmacy practice. But as highlighted by journal editors in the Granada Statements, there is no consensus on these terms...
IMPORTANCE: Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection is paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for glaucoma screening using fundus images co...
PURPOSE: To critically examine the current state of machine learning (ML) models including patient-reported outcome measure (PROM) scores in cancer research, by investigating the reporting quality of currently available studies and proposing areas of...