Invariant Representation Learning in Multimedia Recommendation with Modality Alignment and Model Fusion by Xinghang Hu, Haiteng Zhang

“…However, existing methods may learn a recommendation model from spurious features, i.e., appearing to be related to an outcome but actually having no causal relationship with the outcome, leading to poor generalization ability. …”
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Business Models for Circular Economy and Sustainable Development: the Case of Lease Transactions by Ion Ionașcu, Mihaela Ionașcu

“…The purpose of this paper is to discuss the features of leasing as a business model in the circular economy, which is presumed to support sustainable development by product recirculation and driving economic performance. …”
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Magnetic resonance imaging (MRI) radiomics in paediatric neuro-oncology: A systematic review of clinical applications, feature interpretation, and biological insights in the ch... by Teesta Mukherjee, Omid Pournik, Theodoros N Arvanitis

“…It assesses various approaches used in image pre-processing, tumour segmentation, feature extraction, and predictive model development to understand their accuracy and outcome, while it aims to understand the biological meaning and interpretation of radiomic features. …”
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Design of Pay-for-Performance Programs Affects Clinical Staff Perceptions of HPV Vaccine Incentives: Evidence from a US Survey by Justin G. Trogdon PhD, Kathryn Brignole MSc, Tara Licciardello Queen PhD

“…This study reports how 3 design features (size of incentive, who is responsible, and target goal) affect clinical staff perceptions of pay-for-performance (P4P) for HPV vaccination. …”
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A Small Target Pedestrian Detection Model Based on Autonomous Driving by Yang Zhang, Shuaifeng Zhang, Dongrong Xin, Dewang Chen

“…To improve the accuracy of small-target pedestrian detection and the anti-interference ability of the model, a small-target pedestrian detection model that fuses residual networks and feature pyramids is proposed. …”
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Emotion Recognition Model of EEG Signals Based on Double Attention Mechanism by Yahong Ma, Zhentao Huang, Yuyao Yang, Shanwen Zhang, Qi Dong, Rongrong Wang, Liangliang Hu

“…DACB also introduces dot product attention mechanisms to learn the importance of spatial and temporal features, effectively improving the model’s accuracy. …”
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An interpretable electrocardiogram-based model for predicting arrhythmia and ischemia in cardiovascular disease by Tanjila Alam Sathi, Rafsan Jany, Razia Zaman Ela, AKM Azad, Salem Ali Alyami, Md Azam Hossain, Iqram Hussain

“…We designed a predictive framework utilizing boosting ML algorithms, enhanced by explainable artificial intelligence (XAI) techniques, to ensure high predictive performance in model interpretation. Results: The histogram gradient boosting classifier demonstrated superior classification performance, achieving an overall accuracy of 90 % in predicting heart disease based on ECG fiducial features. …”
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Estimate Programmatic Effort using the Traditional COCOMO Model and Neural Networks by Jamal Al-Din Sayed Majeed, Isra Majeed Qabaa

“…Estimation models in software engineering are used to predict some important and future features for software project such as effort estimation for developing software projects. …”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…This approach resolves the issues of excessive iterations and high computational costs associated with conventional hyperparameter optimization methods, significantly enhancing the model’s predictive performance. The model’s prediction performance is evaluated using mainstream metrics such as the Mean Absolute Percentage Error (MAPE), Coefficient of Determination (R²), Root Mean Square Error (RMSE), robustness analysis, overfitting analysis, and grey relational analysis. …”
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Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…Sentiment analysis is a key branch of Natural language processing (NLP) and new models with better performance can boost the development of machine learning. …”
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Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

“…The random forest algorithm and whale optimization algorithm were introduced in the construction of the prediction model of concrete dam deformation based on WOA-RFR to improve the prediction accuracy and model performance. …”
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An analytical delay model for multi-class and lane-free traffic condition. by Vinaya S Mattungal, Lelitha Devi Vanajakshi

“…The model's efficacy is demonstrated through comparison with conventional in practice delay models, showing its superior performance. …”
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An interpretable machine learning-assisted diagnostic model for Kawasaki disease in children by Mengyu Duan, Zhimin Geng, Lichao Gao, Yonggen Zhao, Zheming Li, Lindong Chen, Pekka Kuosmanen, Guoqiang Qi, Fangqi Gong, Gang Yu

“…When relying on the top 10 most important features, the model’s AUC remains at 0.9757. The proposed model can assist clinicians in making early and accurate diagnoses of KD. …”
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Active Contour Models Based on Block Similarity for Multiple Objects Segmentation by Guoqi Liu, Jinjin Wei

“…Experimental results show the proposed method could segment images with multiple targets, and it improves the robust segmentation performance of sequence of image when the features of multiobjects are missing or misleading.…”
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Research and Application of Heart Disease Prediction Model Based on Machine Learning by Bao Yongli

“…A heart disease dataset was used in the study, and multiple ML models were used to analyze multiple key health features, and the model performance was verified through a test set. …”
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A dynamic preference recommendation model based on spatiotemporal knowledge graphs by Xinyu Fan, Yinqin Ji, Bei Hui

“…Constructed by knowledge graphs, the model integrates spatiotemporal features and takes into account the dynamic preferences of users across various temporal, spatial, and situational contexts. …”
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Adaptive Noise-Powered Diffusion Model for Efficient and Accurate Object Detection by Xingyu Zou, Kaixu Han, Xinle Zhang, Wenhao Wang, Ning Wu

“…DifAda employs an adaptive noise mechanism that blends random noise with latent codes, enhancing object candidate utilization and improving object localization. Our model features a simplified decoder structure by employing a single decoder layer and utilizes an adaptive interaction mechanism to further refine feature representations, leading to improved performance with fewer parameters. …”
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YOLO-GCOF: A Lightweight Low-Altitude Drone Detection Model by Wanjun Yu, Kongxin Mo

“…The HSFPN architecture enables efficient multi-scale feature fusion, and the CSA module optimizes feature selection across scales, improving the model’s ability to detect key features using both scale and coordinate information. …”
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Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis by C. R. Dhivyaa, K. Nithya, C. Sathiya Kumar, R. Sudhakar

“…In the first approach, TrioFusionNet integrates three Convolutional models known as ResNet-50, InceptionV3, and EfficientB4 to detect deep features. …”
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Canopy extraction of mango trees in hilly and plain orchards using UAV images: Performance of machine learning vs deep learning by Yuqi Yang, Tiwei Zeng, Long Li, Jihua Fang, Wei Fu, Yang Gu

“…Subsequently, Mixed Dataset-HR-Net and ETC-CHM (Canopy height model) models were developed based on these optimal models, and their performance was evaluated for canopy segmentation and area extraction in four representative regions. …”
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