Results 251 to 260 of about 1,347,746 (312)
Enhancing products performance evaluation through hybrid DistilRoBERTa and BiGRU models. [PDF]
Ullah S +6 more
europepmc +1 more source
Stratified vs. Random Sampling Effects on F1-Score Variance in Code Vulnerability Detection
This report synthesises findings from 12 peer-reviewed papers addressing the following research question: How does stratified sampling versus random sampling affect the variance of F1-scores for Llama3 and Codestral in code vulnerability detection tasks under high data contamination rates.
openaire +1 more source
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng +4 more
wiley +1 more source
Predicting future surgical steps during MCA aneurysm clipping using a multimodal transformer. [PDF]
On TJ +6 more
europepmc +1 more source
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source
Image-Based Classification of Concrete Carbonation Using YOLO Models. [PDF]
Aydın Y +4 more
europepmc +1 more source
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
Comprehensive benchmarking of deep learning architectures for multiclass histopathological classification of oral epithelial lesions. [PDF]
Bharti A +7 more
europepmc +1 more source
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source
Recognition and linking of discontinuous named entities in healthcare: a comparative performance analysis. [PDF]
Alhassan A +6 more
europepmc +1 more source

