Antithrombotic therapy for secondary Stroke prevention in patients with symptomatic large artery atherosclerosis and atrial fibrillation (FIB-CAS study) A single-center experience.

Introduction: Atrial fibrillation (AF) and large artery atherosclerotic diseases are major causes of ischemic stroke and their coexistence increases the risk of stroke and mortality. Research on antithrombotic strategies for AF patients with symptomatic large artery atherosclerosis is limited. This study aims to report a single center's experience regarding the antithrombotic regimens prescribed for this population and the association with stroke recurrence and hemorrhagic events.

Ethical and Bias Considerations in Artificial Intelligence (AI)/Machine Learning.

As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications and potential biases within such integrated AI models will require careful scrutiny. Ethics and bias are important considerations in our practice settings, especially as increased number of machine learning (ML) systems are being integrated within our various medical domains. Such machine learning based systems, have demonstrated remarkable capabilities in specified tasks such as but not limited to image recognition, natural language processing, and predictive analytics.

Research active medical imaging professionals in Australian metropolitan health services embrace opportunities and can overcome obstacles to engage in research: A mixed methods study.

Introduction: A minority of medical imaging professionals within Australian metropolitan healthcare services are engaging in research activity as part of an emerging research culture. This study aimed to explore the characteristics and experience of medical imaging professionals who engage in research to identify contextual and individual factors that empower them to participate in research.

Methods: A mixed methods observational study consisting of quantitative (survey) and qualitative (semi-structured interview) components using an interpretative description approach was completed with research active medical imaging professionals (radiographers, nuclear medicine technologists and sonographers).

Pelvic congestion syndrome: Not all pelvic pain is gynaecological.

Background: Chronic pelvic pain is a debilitating but common syndrome that is a burden both for patients and health systems. Pelvic congestion syndrome (PCS) contributes to 30-40% of patients presenting with chronic pelvic pain where no other cause is identified. However, PCS is poorly understood, underdiagnosed and undertreated, with the average time to diagnosis being reported as up to four years after initial presentation.