Results 191 to 200 of about 46,171 (307)
Vehicle Classification Using an Imbalanced Dataset Based on a Single Magnetic Sensor. [PDF]
Xu C, Wang Y, Bao X, Li F.
europepmc +1 more source
Traffic Sign Recognition System for Imbalanced Dataset [PDF]
Yildiz Aydin +2 more
openaire +3 more sources
Multidrug‐resistant Vibrio infections are rising rapidly and threaten coastal populations worldwide. This study introduces D‐zp37, a chirality‐engineered antimicrobial peptide with exceptional potency against resistant Vibrio species. D‐zp37 kills planktonic cells, blocks mixed‐species biofilms, disrupts essential bacterial stress responses, and shows ...
Ping Zeng +11 more
wiley +1 more source
Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset. [PDF]
Agraz M +3 more
europepmc +1 more source
Risk factor analysis of device-related infections: value of re-sampling method on the real-world imbalanced dataset. [PDF]
Feng XF, Yang LC, Tan LZ, Li YG.
europepmc +1 more source
In this article, Shuai and colleagues demonstrate that metabolic remodeling drives self‐diploidization in murine haploid ESCs (haESCs). Mitochondrial dysfunction and imbalanced pyruvate metabolism underlie this process. Genome‐wide screening using haESCs identifies key mitochondrial quality‐control related genes, enabling a metabolism‐based medium that
Yi Fu +11 more
wiley +1 more source
Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset. [PDF]
Chen YF +6 more
europepmc +1 more source
Personalized Network‐Guided Neuromodulation Enhances Human Working Memory
A personalized neuromodulation framework combining individualized functional brain network targeting with real‐time neural decoding is introduced. Using concurrent TMS–fMRI, participant‐specific stimulation targets and optimal frequencies are identified. Only optimal‐frequency stimulation improves working memory across sessions.
Ahsan Khan +13 more
wiley +1 more source
Generative AI‐Driven Accelerated Discovery of Passivation Molecules for Perovskite Solar Cells
A generative artificial intelligence (AI) framework combining a discriminative machine learning model (SMILES‐X) and a generative language model (GPT‐2) autonomously discovers new molecular passivators for perovskite solar cells (PSCs). Through an iterative design loop, over 100 000 candidates are generated and screened, and randomly selected molecules
Adroit T. N. Fajar +7 more
wiley +1 more source

