Can artificial intelligence improve patient educational material readability? A systematic review and narrative synthesis.

Enhancing patient comprehension of their health is crucial in improving health outcomes. The integration of artificial intelligence (AI) in distilling medical information into a conversational, legible format can potentially enhance health literacy. This review aims to examine the accuracy, reliability, comprehensiveness and readability of medical patient education materials (PEMs) simplified by AI models.

The sustainability impacts of a web-based outpatient booking application.

Background: Climate change is a critical global issue, impacting ecosystems, economies and communities worldwide. The shift from paper-based to digital systems is becoming increasingly prevalent across industries, with downstream positive impacts on sustainability. In 2020, Austin Health, a public tertiary hospital in Victoria, Australia, adopted a web-based outpatient booking application, which succeeded the prior paper-based system.

Teaching Strategies in Interventional Radiology: A Narrative Review of the Literature.

Introduction: Interventional radiology (IR) is a rapidly developing speciality where innovation-especially in teaching practices-is vital. With workforce and capacity shortages, synthesis of classical educational theories and novel strategies utilising virtual reality (VR) and artificial intelligence (AI) provide opportunities to make teaching as efficient and effective as possible. The aim of this review is to examine the literature on different approaches in IR teaching and learning in undergraduates and postgraduates.

Incidental findings in research brain MRI: Definition, prevalence and ethical implications.

Radiological incidental findings (IFs) are previously undetected abnormalities which are unrelated to the original indication for imaging and are unexpectedly discovered. In brain magnetic resonance imaging (MRI), the prevalence of IFs is increasing. By reviewing the literature on IFs in brain MRI performed for research purposes and discussing ethical considerations of IFs, this paper provides an overview of brain IF research results and factors contributing to inconsistencies and considers how the consent process can be improved from an ethical perspective.

Development a novel nano-platform for Thrombolysis acceleration by Thrombin sensitive polymer-peptide hybrid nancapsules.

According to the importance of time in treatment of thrombosis disorders, faster than current treatments are required. For the first time, this research discloses a novel strategy for rapid dissolution of blood clots by encapsulation of a fibrinolytic (Reteplase) into a Thrombin sensitive shell formed by polymerization of acrylamide monomers and bisacryloylated peptide as crosslinker. Degradability of the peptide units in exposure to Thrombin, creates the Thrombin-sensitive Reteplase nanocapsules (TSRNPs) as a triggered release system.

Evaluation of a passive arm-support exoskeleton for surgical team members: Results from live surgeries.

Background: Musculoskeletal symptoms and injuries adversely impact the health of surgical team members and their performance in the operating room (OR). Though ergonomic risks in surgery are well-recognized, mitigating these risks is especially difficult. In this study, we aimed to assess the impacts of an exoskeleton when used by OR team members during live surgeries.

Verification of a simplified aneurysm dimensionless flow parameter to predict intracranial aneurysm rupture status.

Objectives: Aneurysm number (An) is a novel prediction tool utilizing parameters of pulsatility index (PI) and aneurysm geometry. An has been shown to have the potential to differentiate intracranial aneurysm (IA) rupture status. The objective of this study is to investigate the feasibility and accuracy of An for IA rupture status prediction using Australian based clinical data.

High-frequency optical coherence tomography for endovascular management of cerebral aneurysms.

Endovascular management of intracranial aneurysms has become the mainstay of treatment in recent years; however, retreatment rates remain as high as 1 in 5. High-frequency optical coherence tomography (HF-OCT) is an emerging imaging modality for the assessment, treatment and follow-up of cerebral aneurysms. EMBASE and SCOPUS databases were searched for studies relating to the management of intracranial aneurysm with OCT.

A Qualitative Systematic Review of Endovascular Management of Renal Artery Aneurysms.

Purpose: To perform a qualitative systematic review of endovascular management of renal artery aneurysms (RAAs).

Materials And Methods: A comprehensive electronic search of PubMed, MEDLINE, Embase, Google Scholar, and Cochrane databases from 2000 to 2022 was performed using the search terms "renal artery," "aneurysm," and "endovascular." Means of outcome measures were calculated with a primary end point focused on RAA-related mortality and rupture.

Dual Layer vs Single Layer Woven EndoBridge Device in the Treatment of Intracranial Aneurysms: A Propensity Score-Matched Analysis.

Background: The Woven EndoBridge (WEB) devices have been used for treating wide neck bifurcation aneurysms (WNBAs) with several generational enhancements to improve clinical outcomes. The original device dual-layer (WEB DL) was replaced by a single-layer (WEB SL) device in 2013. This study aimed to compare the effectiveness and safety of these devices in managing intracranial aneurysms.

Stent-assisted Woven EndoBridge device for the treatment of intracranial aneurysms: an international multicenter study.

Objective: The Woven EndoBridge (WEB) device is an intrasaccular flow disruptor designed for wide-necked bifurcation aneurysms. These aneurysms may require the use of a concomitant stent. The objective of this study was to determine the clinical and radiological outcomes of patients undergoing stent-assisted WEB treatment.

Machine learning prediction of tree species diversity using forest structure and environmental factors: a case study from the Hyrcanian forest, Iran.

The Hyrcanian forest is a global biodiversity hotspot that harbors many endemic and endangered tree species, but its tree diversity is threatened by various human-induced disturbances, such as logging, grazing, and urbanization. To address this issue, we conducted a study using three machine learning methods, i.e.

The effect of corrective exercises on musculoskeletal disorders among the older adults residing in a nursing home in Rasht, Guilan, Iran.

Background: Ageing causes changes in the function of musculoskeletal systems and disability, and injury among older adults. This study aimed to determine the effect of corrective exercises on musculoskeletal disorders among older adults residing in a nursing home in Iran.

Method: This controlled clinical trial study was conducted on 58 older adults (29 samples in each group).

Occult contrast retention post-thrombectomy on 24-h follow-up dual-energy CT: Associations and impact on imaging analysis.

Background: Following reperfusion treatment in ischemic stroke, computed tomography (CT) imaging at 24 h is widely used to assess radiological outcomes. Even without visible hyperattenuation, occult angiographic contrast may persist in the brain and confound Hounsfield unit-based imaging metrics, such as net water uptake (NWU).

Aims: We aimed to assess the presence and factors associated with retained contrast post-thrombectomy on 24-h imaging using dual-energy CT (DECT), and its impact on the accuracy of NWU as a measure of cerebral edema.

Long-Term Follow-Up of Cerebral Aneurysms Completely Occluded at 6 Months After Intervention with the Woven EndoBridge (WEB) Device: a Retrospective Multicenter Observational Study.

The Woven EndoBridge (WEB) device has been widely used to treat intracranial wide neck bifurcation aneurysms. Initial studies have demonstrated that approximately 90% of patients have same or improved long-term aneurysm occlusion after the initial 6-month follow up. The aim of this study is to assess the long-term follow-up in aneurysms that have achieved complete occlusion at 6 months.

Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging.

Background: Deep learning (DL) algorithms are playing an increasing role in automatic medical image analysis.

Purpose: To evaluate the performance of a DL model for the automatic detection of intracranial haemorrhage and its subtypes on non-contrast CT (NCCT) head studies and to compare the effects of various preprocessing and model design implementations.

Methods: The DL algorithm was trained and externally validated on open-source, multi-centre retrospective data containing radiologist-annotated NCCT head studies.