Accurate preoperative prediction of erectile dysfunction (ED) is important
for counseling patients undergoing radical prostatectomy. While clinical
features are established predictors, the added value of preoperative MRI
remains underexplored. We i... read more
The respiratory virus known as human metapneumovirus (hMPV) is linked to seasonal outbreaks and primarily affects elderly people and young children. Infodemiology, which uses digital data sources, including social media, online news, and search trend... read more
Efficient and simultaneous detection of coexisting metal ions is essential for preserving water quality and mitigating ecological risks during environmental emergencies. However, traditional methods often fall short, either lacking the sensitivity re... read more
Personalized generation in T2I diffusion models aims to naturally incorporate
individual user preferences into the generation process with minimal user
intervention. However, existing studies primarily rely on prompt-level modeling
with large-scale... read more
Physics-Informed Neural Networks (PINNs) show significant potential for
solving inverse problems, especially when observations are limited and sparse,
provided that the relevant physical equations are known. We use PINNs to
estimate smooth velocity... read more
Food delivery platforms face the challenge of helping users navigate vast
catalogs of restaurants and dishes to find meals they truly enjoy. This paper
presents RED, an automated recommendation system designed for iFood, Latin
America's largest on-... read more
Despite their success in image classification, modern convolutional neural
networks (CNNs) exhibit fundamental limitations, including data inefficiency,
poor out-of-distribution generalization, and vulnerability to adversarial
perturbations. The pr... read more
This commentary evaluates the study by Li et al. on the use of artificial intelligence (AI) for patient selection in cosmetic surgery. While the integration of AI into aesthetic decision-making is promising, we raise concerns regarding methodological... read more
Remote sensing object detection has recently emerged as one of the challenging topics in the field of deep learning applications due to the demand for both high detection performance and computational efficiency. To address these problems, this study... read more
Dexterous grasp datasets are vital for embodied intelligence, but mostly
emphasize grasp stability, ignoring functional grasps needed for tasks like
opening bottle caps or holding cup handles. Most rely on bulky, costly, and
hard-to-control high-DO... read more
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