Results 111 to 120 of about 115,711 (260)
Artificial Intelligence for Bone: Theory, Methods, and Applications
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
Regular Factors of Regular Graphs from Eigenvalues [PDF]
Let $r$ and $m$ be two integers such that $r\geq m$. Let $H$ be a graph with order $|H|$, size $e$ and maximum degree $r$ such that $2e\geq |H|r-m$. We find a best lower bound on spectral radius of graph $H$ in terms of $m$ and $r$. Let $G$ be a connected $r$-regular graph of order $|G|$ and $ k < r$ be an integer.
openaire +3 more sources
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
To address challenges in urban building digitization, such as data redundancy, structural ambiguity, and boundary inaccuracy, this paper proposes a topological reconstruction method integrating deep semantic segmentation and adjacency constraints ...
Ruihan Yao +5 more
doaj +1 more source
Regular character degree graphs
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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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
This study introduces a framework that combines graph neural networks with causal inference to forecast recurrence and uncover the clinical and pathological factors driving it. It further provides interpretability, validates risk factors via counterfactual and interventional analyses, and offers evidence‐based insights for treatment planning ...
Jubair Ahmed +3 more
wiley +1 more source
gnSPADE integrates gene‐network structures into a probabilistic topic modeling framework to achieve reference‐free cell‐type deconvolution in spatial transcriptomics. By embedding gene connectivity within the generative process, gnSPADE enhances biological interpretability and accuracy across simulated and real datasets, revealing spatial organization ...
Aoqi Xie, Yuehua Cui
wiley +1 more source
SmartDetectAI: An AI‐Powered Web App for Real‐Time Colorimetric Detection of Heavy Metals in Water
SmartDetectAI integrates silver nanoparticle‐based colorimetric sensing with an AI‐powered web app for rapid, on‐site detection of toxic heavy metals in water. By combining aggregation‐driven optical changes with machine learning analysis of red ‐ green ‐ blue values, the platform achieves portable, low‐cost, and accurate monitoring of Hg‐ and Cd‐based
Nishat Tasnim +9 more
wiley +1 more source
EC-PGMGR: Ensemble Clustering Based on Probability Graphical Model With Graph Regularization for Single-Cell RNA-seq Data. [PDF]
Zhu Y +5 more
europepmc +1 more source

