Publications by authors named "A S Grove"
Background: A fully automated artificial intelligence-based tool was developed to detect and quantify femoral component subsidence between serial radiographs. However, it did not account for measurement errors due to leg position differences, such as rotation or flexion, between comparative radiographs. If there are small differences in rotation or flexion of the leg between comparative radiographs, the impact on subsidence measurement is unclear.
View Article and Find Full Text PDFBackground: We present an automated image ingestion pipeline for a knee radiography registry, integrating a multilabel image-semantic classifier with conformal prediction-based uncertainty quantification and an object detection model for knee hardware.
Methods: Annotators retrospectively classified 26,000 knee images detailing presence, laterality, prostheses, and radiographic views. They further annotated surgical construct locations in 11,841 knee radiographs.
Background: Australia's clinical trials sector is highly productive with continued sector investment needed to enhance research impact. Generating economic evidence alongside trials has the potential to facilitate the implementation of trial results into practice. Ascertaining the use of health economic evaluations alongside clinical trials can assist in determining whether clinical trials fully realize and operationalize their potential to change policy and practice.
View Article and Find Full Text PDFArticle Synopsis
- Chronic migraine affects 2-4% of adults globally and recent advances in expensive medications have prompted a review of their clinical and cost-effectiveness.
- The study analyzed data from randomised controlled trials involving 7352 adults and compared six different medications, including calcitonin gene-related peptide monoclonal antibodies, Botox, and topiramate, against placebo.
- Results showed that calcitonin gene-related peptide monoclonal antibodies ranked highest in reducing headache days and improving quality of life, while topiramate was less effective compared to these newer treatments.
Objectives: To examine the accuracy and impact of artificial intelligence (AI) software assistance in lung cancer screening using CT.
Methods: A systematic review of CE-marked, AI-based software for automated detection and analysis of nodules in CT lung cancer screening was conducted. Multiple databases including Medline, Embase and Cochrane CENTRAL were searched from 2012 to March 2023.