AIMS: Provide urologists with a comprehensive understanding to guide the optimal and evidence-based utilization of VUDS in contemporary practice. read more
Journal of chemical information and modeling
Aug 5, 2025
Machine learning has been increasingly utilized in the field of biomedical research to accelerate the drug discovery process. In recent years, the emergence of quantum computing has led to the extensive exploration of quantum machine learning algorit... read more
Large-scale pre-training frameworks like CLIP have revolutionized multimodal
learning, but their reliance on web-scraped datasets, frequently containing
private user data, raises serious concerns about misuse. Unlearnable Examples
(UEs) have emerge... read more
Generating longitudinal and multi-layered big biological data is crucial for effectively implementing artificial intelligence (AI) and systems biology approaches in characterising whole-body biological functions in health and complex disease states. ... read more
Deep learning-based semantic segmentation models achieve impressive results
yet remain limited in handling distribution shifts between training and test
data. In this paper, we present SDGPA (Synthetic Data Generation and
Progressive Adaptation), a... read more
PURPOSE OF REVIEW: Although effective patient safety education is critical to reducing medical errors, little guidance exists on best practices for patient safety curricula. This review explores the current state of patient safety education in anesth... read more
Adversarial perturbations are useful tools for exposing vulnerabilities in
neural networks. Existing adversarial perturbation methods for object detection
are either limited to attacking CNN-based detectors or weak against
transformer-based detecto... read more
Robots operating in human-centric or hazardous environments must proactively
anticipate and mitigate dangers beyond basic obstacle detection. Traditional
navigation systems often depend on static maps, which struggle to account for
dynamic risks, s... read more
With the proliferation of Large Language Models (LLMs), the detection of
misinformation has become increasingly important and complex. This research
proposes an innovative verifiable misinformation detection LLM agent that goes
beyond traditional t... read more
While large language models (LLMs) have achieved remarkable success in
providing trustworthy responses for knowledge-intensive tasks, they still face
critical limitations such as hallucinations and outdated knowledge. To address
these issues, the r... read more
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