Background: The onset of the coronavirus disease 2019 (COVID-19) outbreak caused major interruptions to the entire healthcare network affecting referral, diagnosis and treatment pathways with the potential to affect cancer treatment outcomes. In Ireland a national lockdown was initiated in March 2020 involving a stay-at-home order with a limitation on travel, social interactions and closure of schools, universities and childcare facilities. We designed a retrospective study comparing treatment outcomes for patients with oropharyngeal cancer treated before and during the COVID pandemic.
View Article and Find Full Text PDFPurpose: In March 2020, a 1-week ultrahypofractionated adjuvant breast radiation therapy schedule, 26 Gy in 5 fractions, and telehealth were adopted to reduce the risk of COVID-19 for staff and patients. This study describes real-world 1-year late toxicity for ultrahypofractionation (including a sequential boost) and patient perspectives on this new schedule and telehealth workflows.
Methods And Materials: Consecutive patients were enrolled between March and August 2020.
Deep learning techniques hold immense promise for advancing medical image analysis, particularly in tasks like image segmentation, where precise annotation of regions or volumes of interest within medical images is crucial but manually laborious and prone to interobserver and intraobserver biases. As such, deep learning approaches could provide automated solutions for such applications. However, the potential of these techniques is often undermined by challenges in reproducibility and generalizability, which are key barriers to their clinical adoption.
View Article and Find Full Text PDFBackground: Enhancing efficiency is crucial in addressing the escalating scarcity of healthcare resources. It plays a pivotal role in achieving Universal Health Coverage (UHC), with the ultimate goal of ensuring health equity for all. A fundamental strategy to bolster efficiency involves pinpointing the underlying causes of inefficiency within the healthcare system through empirical research.
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