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Safety-assured high-speed navigation for MAVs.
Sci Robot
January 2025
Department of Mechanical Engineering, University of Hong Kong, Pokfulam, Hong Kong, China.
Micro air vehicles (MAVs) capable of high-speed autonomous navigation in unknown environments have the potential to improve applications like search and rescue and disaster relief, where timely and safe navigation is critical. However, achieving autonomous, safe, and high-speed MAV navigation faces systematic challenges, necessitating reduced vehicle weight and size for high-speed maneuvering, strong sensing capability for detecting obstacles at a distance, and advanced planning and control algorithms maximizing flight speed while ensuring obstacle avoidance. Here, we present the safety-assured high-speed aerial robot (SUPER), a compact MAV with a 280-millimeter wheelbase and a thrust-to-weight ratio greater than 5.
View Article and Find Full Text PDFImproved Outcomes and Resource Use With Normothermic Machine Perfusion in Liver Transplantation.
JAMA Surg
January 2025
Division of Transplant Surgery, Department of Surgery, Mayo Clinic Arizona, Phoenix.
Importance: Normothermic machine perfusion (NMP) has been shown to reduce peritransplant complications. Despite increasing NMP use in liver transplant (LT), there is a scarcity of real-world clinical experience data.
Objective: To compare LT outcomes between donation after brain death (DBD) and donation after circulatory death (DCD) allografts preserved with NMP or static cold storage (SCS).
scHNTL: single-cell RNA-seq data clustering augmented by high-order neighbors and triplet loss.
Bioinformatics
January 2025
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Sichuan 611756, China.
Motivation: The rapid development of single-cell RNA sequencing (scRNA-seq) has significantly advanced biomedical research. Clustering analysis, crucial for scRNA-seq data, faces challenges including data sparsity, high dimensionality, and variable gene expressions. Better low-dimensional embeddings for these complex data should maintain intrinsic information while making similar data close and dissimilar data distant.
View Article and Find Full Text PDFGenerative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments.
Eur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
Prevalence of psoriatic arthritis in Italy: insights from the multicentric MAPSI study.
Front Med (Lausanne)
January 2025
S.C. Reumatologia, ASL3 Genovese, Genoa, Italy.
Introduction: Psoriatic arthritis (PsA) is a chronic inflammatory arthropathy associated with cutaneous psoriasis (PsO), first defined by Moll and Wright. Initially perceived as relatively benign, PsA is now recognized for its chronic, progressive, and destructive nature, significantly impacting patients' quality of life, similar to Rheumatoid Arthritis (RA). Globally, PsA represents about 20% of cases in early arthritis clinics, posing diagnostic and management challenges.
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