Machine learning-based prognostic modeling integrating PANoptosis in head and neck squamous cell carcinoma by Chen Li, Jiajing Lu, Jialin Zhu, Tao Zhou, Qijie Shen, Bikun Huang, Qingsong Li

“…A prognostic model was constructed using 101 machine learning algorithms and their combinations, with TCGA-HNSCC as the training set and GSE41613 and GSE65858 as validation sets. …”
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Pix2Pix-Based Modelling of Urban Morphogenesis and Its Linkage to Local Climate Zones and Urban Heat Islands in Chinese Megacities by Mo Wang, Ziheng Xiong, Jiayu Zhao, Shiqi Zhou, Qingchan Wang

“…This study employed the Conditional Generative Adversarial Network (cGAN) of the Pix2Pix algorithm as a predictive model to simulate 3D urban morphologies aligned with Local Climate Zone (LCZ) classifications. …”
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An In-Depth Tutorial on BJTU-RAO Bogie Datasets for Fault Diagnosis by Yong Qin, Yiran Wang, Zhaojun Steven Li, Biao Wang, Ao Ding, Chengcheng Wang, Yuanjing Qin, Yang Wang

“…Train fault diagnosis, predictive maintenance, and algorithms evaluation become crucial to ensure operational safety. …”
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Intersections of Big Data and IoT in Academic Publications: A Topic Modeling Approach by Diana-Andreea Căuniac, Andreea-Alexandra Cîrnaru, Simona-Vasilica Oprea, Adela Bâra

“…Topic 6 focuses on technical aspects such as <i>modeling, system performance and prediction algorithms</i>. It delves into the efficiency of IoT networks with terms like “accuracy”, “power” and “performance” standing out.…”
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Deep Learning Applications in Ionospheric Modeling: Progress, Challenges, and Opportunities by Renzhong Zhang, Haorui Li, Yunxiao Shen, Jiayi Yang, Wang Li, Dongsheng Zhao, Andong Hu

“…Looking ahead, research will focus on developing hybrid models that integrate physical modeling with deep learning, exploring adaptive learning algorithms and multi-modal data fusion techniques to enhance long-term predictive capabilities, particularly in addressing the impact of climate change on the ionosphere. …”
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Delivering data: A real-world dataset for last-mile delivery optimizationZenodo by Anna Vrani, Savvas D. Apostolidis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos

“…The collected matrices were processed and structured for direct use in VRP algorithms.The dataset offers substantial reuse potential by serving as a benchmark for evaluating VRP algorithms, enabling the comparison of optimization methods based on real-world logistics problems. …”
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Machine Learning-Based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction by Jayroop Ramesh, Donthi Sankalpa, Rohan Mitra, Salam Dhou

“…Moreover, a novel regression predictive modeling approach is also proposed to achieve the same objective. …”
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ERBB3-related gene PBX1 is associated with prognosis in patients with HER2-positive breast cancer by Shufen Mo, Haiming Zhong, Weiping Dai, Yuanyuan Li, Bin Qi, Taidong Li, Yongguang Cai

“…ERBB3 expression-related differentially expressed genes (DEGs) were identified and intersected with survival status-related DEGs to obtain intersected genes. Three algorithms, LASSO, RandomForest and XGBoost were combined to identify the signature genes. we construct risk models and generate ROC curves for prediction. …”
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A Cloud Computing-Based Intelligent Forecasting Method for Cross-Border E-Commerce Logistics Costs by Yanting Li

“…Aiming at the problems of poor forecasting effect and low accuracy and low efficiency in current cross-border e-commerce logistics cost prediction methods, a cloud computing-based intelligent method for cross-border e-commerce logistics cost prediction is proposed. …”
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Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review by Hesameddin Akbarein, Mohammad Hussein Taaghi, Mahyar Mohebbi, Parham Soufizadeh

“…It also examines the primary machine learning algorithms used in relevant studies, highlighting emerging trends in the field. …”
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Artificial Intelligence in Uropathology by Katia Ramos Moreira Leite, Petronio Augusto de Souza Melo

“…The accurate classification of tumors and identification of prognostic and predictive factors demand specialized expertise and attention. …”
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Automatic detection of fake reviews at marketplaces using expert-based features and consumers’ reactions by A. N. Borodulina, E. V. Mikhalkova

“…The target variable (predicted class) is the ratio of likes and dislikes given to the review by other buyers. …”
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An Overview of the Empirical Evaluation of Explainable AI (XAI): A Comprehensive Guideline for User-Centered Evaluation in XAI by Sidra Naveed, Gunnar Stevens, Dean Robin-Kern

“…Recent advances in technology have propelled Artificial Intelligence (AI) into a crucial role in everyday life, enhancing human performance through sophisticated models and algorithms. However, the focus on predictive accuracy has often resulted in opaque black-box models that lack transparency in decision-making. …”
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Disulfidptosis-related gene in acute myocardial infarction and immune microenvironment analysis: A bioinformatics analysis and validation. by Nan Huang, Chan Liu, Zheng Liu, Haibo Lei

“…Thereafter, seven hub genes were determined by machine learning algorithms, which had potential diagnostic value in AMI. …”
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Improvement in low-homology template-based modeling by employing a model evaluation method with focus on topology. by Wentao Dai, Tingrui Song, Xuan Wang, Xiaoyang Jin, Lizong Deng, Aiping Wu, Taijiao Jiang

“…By combining MEFTop algorithm with FR-t5, a threading program developed by our group, we found that this modified TBM program, which was named FR-t5-M, exhibited significant improvements in predictive abilities for low-homology protein targets. …”
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Phylogenetic quantification of intra-tumour heterogeneity. by Roland F Schwarz, Anne Trinh, Botond Sipos, James D Brenton, Nick Goldman, Florian Markowetz

“…Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data.…”
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Advancements in Remote Sensing for Monitoring and Risk Assessment of Glacial Lake Outburst Floods by Serik Nurakynov, Nurmakhambet Sydyk, Zhaksybek Baygurin, Larissa Balakay

“…Central to this review is the exploration of multi-sensor data fusion for high-resolution lake dynamics mapping, machine learning algorithms for predictive risk modelling, and hydrodynamic simulations for flood propagation analysis. …”
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Early Warning Systems for Plant Diseases in delta regions: Machine Learning Approaches by Biswas Debarghya, Sharma Priti

“…Advanced data analytics and predictive modeling are used in these systems which use this to alert and give the farmers actionable insight into what they should do to prevent the disease from reaching cause irreparable damage before it happens. …”
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Review of Methods and Models for Forecasting Electricity Consumption by Kamil Misiurek, Tadeusz Olkuski, Janusz Zyśk

“…In conclusion, the authors highlight the lack of a universal forecasting approach and the need for further research on hybrid models that combine interpretability with high predictive accuracy. This review can serve as a valuable resource for decision-makers, grid operators, and researchers involved in energy system planning.…”
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Early identification of children with Attention-Deficit/Hyperactivity Disorder (ADHD). by Yang S Liu, Fernanda Talarico, Dan Metes, Yipeng Song, Mengzhe Wang, Lawrence Kiyang, Dori Wearmouth, Shelly Vik, Yifeng Wei, Yanbo Zhang, Jake Hayward, Ghalib Ahmed, Ashley Gaskin, Russell Greiner, Andrew Greenshaw, Alex Alexander, Magdalena Janus, Bo Cao

“…Key predictive factors included EDI subdomain scores, sex, and socioeconomic status. …”
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