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Machine learning

Artificial intelligence in the diagnosis of deep vein thrombosis: A scoping review

Teresa Chen, Ranita Hisham Shunmugam, [ ... ], Kwan Hoong Ng

RGB-based visual encoding of vibration data for gearbox fault diagnosis using U-Net segmentation model

İrfan Kiliç, Gülşah Karaduman, Beyda Tasar, Orhan Yaman

Identifying policy-relevant traffic crash risk factors in Cheongju, South Korea using logistic regression and explainable machine learning

Eun-Ji Lee, Sua Kim, Hyun-Ji Lee, Jae-Hwan Jhong

Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making

Jinghui Hou, Jun Wang, Xiaogang Guo

GARN3: A coarse-grained helix centered technique for RNA 3D structures prediction

Jhonatan Silva, Johanne Cohen, Daniel Cordeiro

Traffic condition prediction for highway within work zones under dynamic traffic organization changes

Feiping Xu, Bohan Liu, [ ... ], Chengcheng Wang

Perceptual no-reference image quality assessment with meta-learning by graph representation learning and multi-scale feature fusion

Yanru Jia, Longsheng Wei

Circ-EnviroPredict: A machine learning-based tool to predict potential involvement of circRNAs with cold and drought stress through a Word2Vec approach

Maria Clara Martins Ferreira, Frederico Schmitt Kremer, Vanessa Galli

Comparative evaluation of deep learning models for plant disease classification with edge-aware performance analysis

Zirije Hasani, Jakup Fondaj, Dionesa Bytyqi, Sufjan Misini

Hybrid quantum-classical neural networks for real-time fault detection in power systems

Hina Hashmi, Aman Kumar, [ ... ], Arshad Hashmi

A Hybrid AI-Mathematical approach for epidemic threshold prediction in metapopulation networks: Integrating physics-guided neural networks with spectral graph theory

Etienne Kouokam

How do theme park attributes influence visitors’ positive emotions? Nonlinear effects and spatial heterogeneity in Shanghai’s theme parks

Xuehui Guo, Xue Li, [ ... ], Chunli Han

Tree ring segmentation performance in highly disturbed trees using deep learning

Joe David Zambrano-Suárez, Jorge Pérez-Martín, Alberto Muñoz-Torrero Manchado, Juan Antonio Ballesteros Cánovas

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