Machine-learning (ML) algorithms are increasingly valuable in health sciences because they can analyze complex, high-dimensional data and detect patterns that may not be easily identified using traditional statistical methods. These models can effici... read more
Antibody-oligonucleotide conjugates (AOCs) effectively integrate the delivery capability of antibodies with the specific gene regulatory function of oligonucleotides, offering a novel strategy for extrahepatic delivery. Unlike antibody-drug conjugate... read more
Optical transport networks rely on reactive fault management, which guarantees service disruption during the onset of soft failures. We present a framework for proactive soft-failure prediction that combines physics-inspired feature engineering, tree... read more
For monitoring the progression of the disease and the efficacy of treatment, it is essential to segment the brain tumor. The majority of the available deep learning models in use today are based on discrete time points without considering the continu... read more
Clinical decision-making often exhibits substantial inter-physician variability when evaluating identical patient data, limiting the reliability of conventional one data-one outcome clinical decision support systems. We developed and validated a Mult... read more
Traditional visual SLAM algorithms, which build maps based on sparse reconstruction, can hardly meet the demands for autonomous navigation and obstacle avoidance in outdoor environment. Therefore, we propose a visual SLAM construction algorithm to ad... read more
This study aims to enhance the overall balance among image detail restoration, structure preservation, and model adaptability in image restoration tasks. The study proposes an optimized Pulse Coupled Neural Network (PCNN) image restoration model inte... read more
As the use of artificial intelligence in education increases, determining student readiness and anxiety has become a necessity; however, the lack of a measurement tool specific to biology education in the literature formed the basis of this study. Th... read more
PollenBB16 is an RGB pollen image dataset of Chilean flora with pixel-accurate instance segmentation masks, whose annotation was fully verified by an expert palynologist to guarantee the taxonomic reliability of every published instance. The dataset ... read more
This study investigates RF magnetron sputtered ZnO thin films doped with Al, Cu, N and co-doped with Al/Cu, followed by post deposition annealing at 300-600 °C. Structural and compositional characterization was performed by X ray diffraction (XRD) an... read more
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