The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer by Danlei Ni, Jiayi Wu, Jingjing Pan, Yajing Liang, Zihui Xu, Zhiying Yan, Kequn Xu, Feifei Wei

“…Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7. …”
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The effectiveness and choice of public pension scheme among Donglan county residents in China by Li Zhu, Zixuan Peng, Qucheng Deng, Xiumei Zhang

“…Methodology Binary logit regression models were conducted using datasets extracted from the Chinese General Social Survey in 2021 and datasets collected through surveying 321 residents in Donglan county, China. …”
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MDCKE: Multimodal deep-context knowledge extractor that integrates contextual information by Hyojin Ko, Joon Yoo, Ok-Ran Jeong

“…An ablation study further corroborated the contribution of each component, resulting in an approximately 6% enhancement in the F1-score across the datasets.…”
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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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Efficient anomaly detection in tabular cybersecurity data using large language models by Xiaoyong Zhao, Xingxin Leng, Lei Wang, Ningning Wang, Yanqiong Liu

“…Experimental results indicate that the TAD-GP framework improves F1 scores by 79.31%, 97.96%, and 59.09% on the CICIDS2017, KDD Cup 1999, and UNSW-NB15 datasets, respectively. Furthermore, the smaller-scale TAD-GP model outperforms larger models across multiple datasets, demonstrating its practical potential in environments with constrained computational resources and requirements for private deployment. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Challenges for credit card fraud monitoring include highly imbalanced datasets and the need for advanced models to detect fraud patterns. …”
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ECP-IEM: Enhancing seasonal crop productivity with deep integrated models. by Ghulam Mustafa, Muhammad Ali Moazzam, Asif Nawaz, Tariq Ali, Deema Mohammed Alsekait, Ahmed Saleh Alattas, Diaa Salama AbdElminaam

“…The proposed model showed very good results in all datasets and showed significant improvement compared to baseline models. …”
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Hyperbolic Graph Convolutional Network Relation Extraction Model Combining Dependency Syntax and Contrastive Learning by Jinzhe Li

“…The experiments indicate that the proposed model in this paper can effectively enhance the performance of relation extraction on public datasets, especially achieving significantly higher precision on datasets with complex sentence structures compared to in-context learning.…”
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Statistical Inference for Heavy-Tailed Burr X Distribution with Applications by Mohamed Kayid, Vasili B. V. Nagarjuna, Mohammed Elgarhy

“…A notable feature is that the associated probability density function can have a right-skewed distribution that approximates symmetry, unimodality, and decreasing values, which makes it well suited for modeling various datasets. The mathematical properties of the new distribution are obtained by calculating the quantile function, ordinary moments, incomplete moments, moment generating function, conditional moment, mean deviation, Bonferroni curve, and Lorenz curve. …”
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Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach by R.M. Haggag, Eman M. Ali, M.E. Khalifa, Mohamed Taha

“…Our framework utilizes The Inception V3 model that is pre-trained on ImageNet and RadImageNet datasets, and we modified the model by adding a new block of six layers to reduce the features’ dimensionality in the feature extraction phase. …”
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Refining the prediction of user satisfaction on chat-based AI applications with unsupervised filtering of rating text inconsistencies by Hae Sun Jung, Jang Hyun Kim, Haein Lee

“…While previous studies have explored leveraging online reviews as indicators of user satisfaction, efficiently collecting and analysing extensive datasets remain a challenge. This research aims to address this challenge by proposing a framework to handle extensive review datasets from the Google Play Store, employing natural language processing with machine learning techniques for sentiment analysis. …”
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Relieving popularity bias in recommendation via debiasing representation enhancement by Junsan Zhang, Sini Wu, Te Wang, Fengmei Ding, Jie Zhu

“…Extensive experiments on three real-world datasets demonstrate that our proposed model outperforms state-of-the-art baselines in recommendation performance, with Recall@20 improvements of 4.2%, 2.4% and 3.6% across the datasets, but also shows significant effectiveness in relieving popularity bias.…”
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Shuffle-PG: Lightweight feature extraction model for retrieving images of plant diseases and pests with deep metric learning by Dong Jin, Helin Yin, Yeong Hyeon Gu

“…To validate the effectiveness of the proposed method, experiments were conducted using plant disease and pest datasets specifically collected for this study. The results show that the proposed Shuffle-PG model uses approximately 20 times fewer parameters and reduces computational costs by an order of magnitude compared to existing benchmark models, while achieving higher mean average precision scores of 97.7 % and 98.8 % for the disease and pest datasets, respectively.…”
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PRESEE: An MDL/MML Algorithm to Time-Series Stream Segmenting by Kaikuo Xu, Yexi Jiang, Mingjie Tang, Changan Yuan, Changjie Tang

“…The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. …”
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A novel carbon emission monitoring method for power generation enterprises based on hybrid transformer model by Yuqiong Jiang, Zhaofang Mao

“…The model was extensively validated on three datasets from three different types of power enterprises. …”
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Deep Learning on 3D Semantic Segmentation: A Detailed Review by Thodoris Betsas, Andreas Georgopoulos, Anastasios Doulamis, Pierre Grussenmeyer

“…Finally, a fruitful discussion of the examined 3DSS methods and datasets is presented to foster new research directions and applications in the field of 3DSS. …”
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Utilizing Machine Learning-based Classification Models for Tracking Air Pollution Sources: A Case Study in Korea by Yelim Choi, Bogyeong Kang, Daekeun Kim

“…By analyzing multidimensional datasets containing a wide range of air pollutants, a machine learning approach has the potential to significantly improve air pollution management and facilitate source tracking. …”
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Prevention or Promotion? Predicting Author's Regulatory Focus by Aswathy Velutharambath, Kai Sassenberg, Roman Klinger

“…To bridge this gap we introduce the novel task of regulatory focus classification from text and present two complementary German datasets – (1) experimentally generated event descriptions and (2) manually annotated short social media texts used for evaluating the generalizability of models on real-world data. …”
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Interpretable and integrative deep learning for discovering brain-behaviour associations by Corentin Ambroise, Antoine Grigis, Josselin Houenou, Vincent Frouin

“…Our framework effectively identifies relevant and stable associations, even with incomplete datasets, while isolating variability of interest from confounding factors.…”
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The Generalization Error Bound for the Multiclass Analytical Center Classifier by Zeng Fanzi, Ma Xiaolong

“…The experiments on benchmark datasets validate the generalization performance of MACM.…”
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