Results 301 to 310 of about 3,002,087 (370)
Evaluating knowledge fusion models on detecting adverse drug events in text. [PDF]
Wegner P, Fröhlich H, Madan S.
europepmc +1 more source
Comparison of Large Language Model with Aphasia
Large language models (LLMs) answer almost all questions fluently but often inaccurately, which resembles a specific type of aphasia in humans. Using a data‐driven analysis called energy landscape analysis, this study reveals similarities in the internal information dynamics between LLMs and the brains of humans with receptive aphasia, such as Wernicke'
Takamitsu Watanabe+4 more
wiley +1 more source
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers. [PDF]
Chen X+5 more
europepmc +1 more source
Defining Name Accessibility using Scope Graphs (Extended Edition) [PDF]
Aron Zwaan, Casper Bach Poulsen
openalex +1 more source
Efficient R‐CHIP HR‐HPV Screening System: The R‐CHIP system utilizes the RPA/CRISPR method, a hand‐driven centrifugal microfluidic device, a smartphone micro‐imaging system, and the ResNet‐18 deep‐learning algorithm to simplify the sample detection process, ensure accurate results, and reduce costs.
Tao Xu+11 more
wiley +1 more source
Biomedical named entity recognition using improved green anaconda-assisted Bi-GRU-based hierarchical ResNet model. [PDF]
Bhushan RC+4 more
europepmc +1 more source
Piezoelectric microdevices, composed of ZnO nanosheets acting as nanogenerators and grown on silicon microparticles, are designed and fabricated to deliver precise electrical cell stimulation. This study optimizes nanosheet growth and microparticle size to enhance electrical cell activation performance while minimizing cellular internalization.
Laura Lefaix+4 more
wiley +1 more source
AMFGNN: an adaptive multi-view fusion graph neural network model for drug prediction. [PDF]
He F+5 more
europepmc +1 more source
Transcriptome Landscape of Cancer‐Associated Fibroblasts in Human PDAC
AP‐1 family members FOS and JUN regulate the malignant phenotype conversion of normal fibroblasts (NFs) to normal‐like cancer‐associated fibroblasts (nCAFs), while transforming growth factor‐β (TGFβ) and interferon‐γ (IFNγ) signals triggers the interconversion between classic myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs), respectively ...
Mengyu Tao+15 more
wiley +1 more source