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Multi-level Factors to Build Confidence and Support in Active Surveillance for Low-Risk Prostate Cancer: A Qualitative Study.
J Gen Intern Med
January 2025
Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Background: Active surveillance (AS) is the guideline-recommended treatment for low-risk prostate cancer and involves routine provider visits, lab tests, imaging, and prostate biopsies. Despite good uptake, adherence to AS, in terms of receiving recommended follow-up testing and remaining on AS in the absence of evidence of cancer progression, remains challenging.
Objective: We sought to better understand urologist, primary care providers (PCPs), and patient experiences with AS care delivery to identify opportunities to improve adherence.
Rome Foundation Working Team Report on overlap in disorders of gut-brain interaction.
Nat Rev Gastroenterol Hepatol
January 2025
Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
In patients with disorders of gut-brain interaction (DGBI), overlapping non-gastrointestinal conditions such as fibromyalgia, headaches, gynaecological and urological conditions, sleep disturbances and fatigue are common, as is overlap among DGBI in different regions of the gastrointestinal tract. These overlaps strongly influence patient management and outcome. Shared pathophysiology could explain this scenario, but details are not fully understood.
View Article and Find Full Text PDFUnsupervised data imputation with multiple importance sampling variational autoencoders.
Sci Rep
January 2025
School of Mathematics and Statistics, Shaoguan University, Shaoguan, 512005, China.
Recently, deep latent variable models have made significant progress in dealing with missing data problems, benefiting from their ability to capture intricate and non-linear relationships within the data. In this work, we further investigate the potential of Variational Autoencoders (VAEs) in addressing the uncertainty associated with missing data via a multiple importance sampling strategy. We propose a Missing data Multiple Importance Sampling Variational Auto-Encoder (MMISVAE) method to effectively model incomplete data.
View Article and Find Full Text PDFUAV selection for high-speed train communication using OTFS modulation.
Sci Rep
January 2025
Computational Learning Theory Team, RIKEN-Advanced Intelligence Project, Fukuoka, 819-0395, Japan.
Providing continuous wireless connectivity for high-speed trains (HSTs) is challenging due to their high speeds, making installing numerous ground base stations (BSs) along the HST route an expensive solution, particularly in rural and wilderness areas. This paper proposes using multiple unmanned aerial vehicles (UAVs) to deliver high data rate wireless connectivity for HSTs, taking advantage of their ability to fly, hover, and maneuver at low altitudes. However, autonomously selecting the optimal UAV by the HST is challenging.
View Article and Find Full Text PDFAvoiding never events in orthopaedics theatres: a quality improvement project.
BMJ Open Qual
January 2025
Trauma & Orthopaedics, Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, UK.
Never events in the operating room are a surgeon's nightmare, with an incidence rate of 54%. These events are highly stressful for theatre staff and significantly compromise patient safety. The aim of this project is to avoid never events in trauma and orthopaedic theatres by ensuring that theatre staff adhere to the surgical pause and imaging pause protocols through regular audits.
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