Results 251 to 260 of about 201,162 (313)

Enhancing products performance evaluation through hybrid DistilRoBERTa and BiGRU models. [PDF]

PLoS One
Ullah S, Khan A, Ullah A, Khan MN, Chohan RT, Aadil F, Khan KU.   +6 more
europepmc   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
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, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Predicting future surgical steps during MCA aneurysm clipping using a multimodal transformer. [PDF]

Front Surg
On TJ, Tangsrivimol JA, Chen J, Xu Y, Li B, Lawton MT, Preul MC.   +6 more
europepmc   +1 more source

Impact of Word Alignment Noise on Cross-Lingual NER F1-Score and Adversarial Robustness

Cross-lingual Named Entity Recognition (NER) leverages knowledge transfer between languages to identify and classify named entities, making it particularly useful for low-resource languages. We show that the data-based cross-lingual transfer method is an effective technique for crosslingual NER and can outperform multilingual language models for low ...
openaire   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
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, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

Image-Based Classification of Concrete Carbonation Using YOLO Models. [PDF]

Materials (Basel)
Aydın Y, Işıkdağ Ü, Nigdeli SM, Bekdaş G, Cakiroglu C.   +4 more
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
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, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Comprehensive benchmarking of deep learning architectures for multiclass histopathological classification of oral epithelial lesions. [PDF]

J Oral Biol Craniofac Res
Bharti A, Kashyap N, Kamboj M, Joshi K, Hooda S, Mishra D, Singh H, Pal D.   +7 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