Diagnostic classification in toxicologic pathology using attention-guided weak supervision and whole slide image features: a pilot study in rat livers by Philip Zehnder, Jeffrey Feng, Trung Nguyen, Philip Shen, Ruth Sullivan, Reina N. Fuji, Fangyao Hu

“…We propose an innovative weakly supervised learning method that leverages minimal annotations, a state-of-the-art self-supervised vision transformer for embedding extraction, and a novel guided attention mechanism that is better suited for heavily imbalanced datasets typical in toxicologic pathology. …”
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Deep learning and smart energy-based lightweight urban power load forecasting model for sustainable urban growth by Haewon Byeon, Azzah AlGhamdi, Ismail Keshta, Mukesh Soni, Sultonali Mekhmonov, Gurpreet Singh

“…Its performance was evaluated through parameter tuning and comparative analysis.ResultsThe DLUPLF model demonstrated improved accuracy in forecasting imbalanced datasets while reducing computational costs. …”
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Intrusion Detection for Wireless Sensor Network Using Particle Swarm Optimization Based Explainable Ensemble Machine Learning Approach by Shaikh Afnan Birahim, Avijit Paul, Fahmida Rahman, Yamina Islam, Tonmoy Roy, Mohammad Asif Hasan, Fariha Haque, Muhammad E. H. Chowdhury

“…The system addresses key challenges such as the imbalanced nature of datasets and the evolving complexity of network attacks. …”
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Linkboost: A Link Prediction Algorithm to Solve the Problem of Network Vulnerability in Cases Involving Incomplete Information by Chengfeng Jia, Jie Ma, Qi Liu, Yu Zhang, Hua Han

“…The key aspect of this algorithm is that it can deal with the imbalanced class distribution present in the network data. …”
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Acidification and Nitrogen Eutrophication of Austrian Forest Soils by Robert Jandl, Stefan Smidt, Franz Mutsch, Alfred Fürst, Harald Zechmeister, Heidi Bauer, Thomas Dirnböck

“…Elevated rates of nitrogen deposition were believed to cause nitrate leaching and imbalanced forest nutrition. We used data from a soil monitoring network to evaluate the trends and current status of the pH and the C : N ratio of Austrian forest soils. …”
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Unveiling the molecular and cellular links between obstructive sleep apnea-hypopnea syndrome and vascular aging by Wei Liu, Le Zhang, Wenhui Liao, Huiguo Liu, Wukaiyang Liang, Jinhua Yan, Yi Huang, Tao Jiang, Qian Wang, Cuntai Zhang, Peifang Wei

“…This review examines the molecular and cellular features common to both OSAHS and VA, highlighting decreased melatonin secretion, impaired autophagy, increased apoptosis, increased inflammation and pyroptosis, increased oxidative stress, accelerated telomere shortening, accelerated stem cell depletion, metabolic disorders, imbalanced protein homeostasis, epigenetic alterations, and dysregulated neurohormonal signaling. …”
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Decreased TNF Levels and Improved Retinal Ganglion Cell Survival in MMP-2 Null Mice Suggest a Role for MMP-2 as TNF Sheddase by Lies De Groef, Manuel Salinas-Navarro, Griet Van Imschoot, Claude Libert, Roosmarijn E. Vandenbroucke, Lieve Moons

“…Pathological conditions in the CNS are therefore often related to imbalanced MMP activities and disturbances of the complex MMP-dependent protease network. …”
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Evaluation of Agronomic Management Practices on Farmers’ Fields under Rice-Wheat Cropping System in Northern India by Dinesh Kumar Singh, Purushottam Kumar, A. K. Bhardwaj

“…Balanced fertilization incurred additional cost of $38 over the imbalanced fertilization and provided additional returns of $180/ha. …”
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Relieving popularity bias in recommendation via debiasing representation enhancement by Junsan Zhang, Sini Wu, Te Wang, Fengmei Ding, Jie Zhu

“…Abstract The interaction data used for training recommender systems often exhibit a long-tail distribution. Such highly imbalanced data distribution results in an unfair learning process among items. …”
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Research on Wood Defects Feature Imbalance Optimization and Recognition by Xiao Wang

“…In this study, the problems are attributed to imbalanced feature distribution of wood defects which are rich in diversity. …”
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Research on medical small sample data classification based on SMOTE and gcForest by Wenchang LIU, Yun WEI, Haoxuan YUAN, Yue GAO

“…Aiming at the problem of poor classification performance in traditional machine learning models caused by shallow model structure and complex data characteristics in small medical sample data, an combine multi- grained improved cascade forest (cgicForest) model was proposed.It enhances the representation learning ability of the model by adding random sampling into the multi-grained scanning and optimizing the transformation features.It also enhances the model's classification ability by updating the cascade forest’s hierarchical structure.Considering category imbalance problems in datasets, the safe-borderline-SMOTE (SBS) algorithm was proposed to dynamic interpolate around the few class samples belonging to the safety boundary, which can improve the quality of training data.The cgicForest was applied for training and learning, thus the SBS-cgicForest classification model was obtained which can support imbalanced medical small samples data.The model is used on three medical datasets for classification experiments.The results show that the performance indexes of the cgicForest model in the classification of medical small sample data with complex characteristics have increased by 4.1～5.4 percentage points, compared with the multi-grained cascade forest (gcForest) model.The performance indexes have increase by 6.6～11.2 percentage points after the combination with SBS algorithm, the F₁ score was 2～2.5 percentage points higher than that obtained by traditional sampling methods.It provides a reference for solving the classification problem of small medical sample data, and includes support for internet of things applications in smart medical scenarios.…”
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Model Optimization Analysis of Customer Churn Prediction Using Machine Learning Algorithms with Focus on Feature Reductions by Seyed Mohammad Sina Mirabdolbaghi, Babak Amiri

“…In light of the evaluation metrics, our model shows a significant improvement in handling imbalanced datasets in churn prediction. Finally, in this paper, interpretability and how the features affect the model’s output are presented by the SHAP method. …”
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Investigation of the Economic Mechanism of Utilizing Distributed Solar Photovoltaic Systems in Iran by Sana Labbafi, Sina Labbafi, Hossein Heirani, Seyedali Sina

“…In this respect, the present research considers Iran as a country with very low electricity prices coupled with very large potentials for utilizing solar energy in the presence of imbalanced electricity supply and demand, with the research objective being an investigation of the required incentive policies to promote the utilization of distributed solar photovoltaic (DSPV) systems in the country. …”
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Exploring mechanisms of insulin action and strategies to treat diabetes by Takayoshi Sasako

“…Aging is regulated by adipokines as well, and it should be considered that aging could be accelerated by ‘imbalanced adipokines’ in patients with a genetic background of progeria. …”
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Vortical waves in a quantum fluid with vector, axial, and helical charges. I. Non-dissipative transport by Sergio Morales-Tejera, Victor E. Ambruş, Maxim N. Chernodub

“…We show that the chirally imbalanced rotating fluid should possess non-reciprocal gapless waves that propagate with different velocities along and opposite to the vorticity vector. …”
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Adaptive Tip Selection for DAG-Shard-Based Federated Learning with High Concurrency and Fairness by Ruiqi Xiao, Yun Cao, Bin Xia

“…Additionally, DSFL outperforms DAG-FL and Chains-FL on both balanced and imbalanced datasets.…”
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Fault Diagnosis of Rolling Bearings Based on Two-step Transfer Learning and EfficientNetV2 by Du Kangning, Ning Shaohui

“…Then, the synthetic minority oversampling technique (SMOTE) oversampling method and the edited nearest neighbors (ENN) under the sampling method are proposed to expand the fault data, reconstructing the class-imbalanced dataset into a class-balanced dataset. Finally, the model is trained on the class-balanced dataset, freezing the model's bottom weights and training the model deeper for a second transfer learning, enabling the model to take control of the failure characteristics of the balanced dataset. …”
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A novel deep learning-based 1D-CNN-optimized GRU approach for heart disease prediction by Jini Mol G., Ajith Bosco Raj T.

“…The minimax scalar transform is applied to first denoise the input data, and then the ENN-smote approach is applied to address the issue of an imbalanced dataset. Secondly, we employ a standard deep learning (DL) methodology. …”
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Emergency Medical Resources Allocation of Periphery for Epidemic Areas: Based on Infectious Diseases Spatial-Temporal Transmission Path by Xuan Zhao, Benhong Peng, Chaoyu Zheng, Anxia Wan

“…People in the epicenter suffer from emergency medical supplies shortage in the early stage of a public health emergency because of imbalanced supply-demand in different regions or areas, which is a key issue in a major infectious disease. …”
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Interocular Shift of Visual Attention Enhances Stereopsis and Visual Acuities of Anisometropic Amblyopes beyond the Critical Period of Visual Development: A Novel Approach by Liwen Huang, Xinghuai Sun, Gang Luo, Shuai Liu, Rui Liu, Behzad Mansouri, Vicky wing lai Wong, Wen Wen, Hong Liu, Ai-Hou Wang

“…Increasing evidence shows that imbalanced suppressive drive prior to binocular combination may be the key factor in amblyopia. …”
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