A multicenter retrospective investigation has demonstrated that a machine learning model analyzing preoperative contrast-enhanced computed tomography scans can noninvasively predict ...
Researchers have introduced an online semantic correlation learning framework that incorporates multi-label supervision to continually align cross-modal latent spaces with ...
Published in the journal Frontiers of Urban and Rural Planning, the study examines a four-year city branding initiative in Longquan, ...
The study, published in Discover Computing, introduces the Trimmed-Mean Federated Chain, or TFC, which aims to address vulnerabilities in distributed ...
Researchers have developed a reinforcement learning framework that autonomously diagnoses and remediates multiple SDN fault types within tens of seconds.
An explainable machine learning pipeline combining XGBoost and SHAP revealed that specific patient knowledge deficits were strongly associated with tuberculosis ...
A study published in Disciplinary and Interdisciplinary Science Education Research demonstrates that artificial intelligence and network analysis can uncover distinct, ...
A hydrological modeling study in Ethiopia's Meki watershed revealed that three decades of agricultural expansion and deforestation drove a 35.58 ...
A narrative review of 23 studies finds that AI and machine learning tools show promise for early eating disorder detection, ...
A new national-scale study published in Geoenvironmental Disasters demonstrates that climate change is primarily redistributing landslide susceptibility across the Nepal ...
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