Publications by authors named "G M Currie"
Purpose: [Tc]Tc-HYNIC-iPSMA is a novel technetium-99m-labelled small molecule inhibitor of the prostate-specific membrane antigen (PSMA) for detecting prostate cancer (PC). The objective of this registry was to collect and evaluate [Tc]Tc-HYNIC-iPSMA patient data and images to establish the safety and tolerability, and clinical utility of this agent in imaging at different stages of PC.
Methods: Patients 18 to 80 years old with primary staging and metastatic PC were eligible.
Background: Allogeneic bone marrow transplantation (BMT) may be a curative treatment for patients with rheumatoid arthritis (RA), but it has serious risks, including death. It is uncertain whether patients would accept the risks and benefits of BMT and participate in clinical trials. We conducted a discrete choice experiment (DCE) to quantify risk tolerance and benefit-risk trade-offs to inform the design of a clinical trial for BMT.
View Article and Find Full Text PDFObjective: To determine whether [F]FDG PET/CT and hematological parameters provide supportive data to determine HPV status in HNSCC patients.
Methods: Retrospective analysis of clinical and diagnostic data from 106 patients with HNSCC: 26.4% HPV-positive and 73.
Article Synopsis
- In Australia, despite nearly 50% of paramedics being female, generative AI like DALL-E 3 reinforces stereotypes by depicting a majority of first responders as male and Caucasian.
- A study conducted in March 2024 generated 82 images of first responders, which were analyzed for gender, age, skin tone, and ethnicity, revealing that 90.8% of characters were male and 90.5% were Caucasian.
- The findings indicate significant bias in AI-generated imagery, showing that the portrayal of paramedics and police officers does not accurately reflect the actual diversity of the workforce in Australia, with generated images depicting 100% of paramedics as male and Caucasian.
Artificial intelligence (AI) has rapidly reshaped the global practice of nuclear medicine. Through this shift, the integration of AI into nuclear medicine education, clinical practice, and research has a significant impact on workforce diversity. While AI in nuclear medicine has the potential to be a powerful tool to improve clinical, research and educational practice, and to enhance patient care, careful examination of the impact of each AI tool needs to be undertaken with respect to the impact on, among other factors, diversity in the nuclear medicine workforce.
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