Trend equation prediction in medical and pharmaceutical studies (the example of respiratory diseases development in children in the region) by O. V. Zhukova, S. V. Kononova, T. M. Konyshkina

“…However, mathematical models and computational algorithms for monitoring, predicting incidence, spread and prevention of various nosologies are still to be developed.…”
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Novel disctete grey Bernoulli seasonal model with a time powter term for predicting monthly carbon dioxide emissions in the United States by Jianming Jiang, Yandong Ban, Sheng Nong

“…This study proposes a more efficient discrete grey prediction model to describe the seasonalvariation trends of carbon dioxide emissions. …”
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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

Subjects: “…Gravity search optimization algorithm…”
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Non-Invasive Techniques for Monitoring and Fault Detection in Internal Combustion Engines: A Systematic Review by Norah Nadia Sánchez Torres, Jorge Gomes Lima, Joylan Nunes Maciel, Mario Gazziro, Abel Cavalcante Lima Filho, Cicero Rocha Souto, Fabiano Salvadori, Oswaldo Hideo Ando Junior

“…Finally, concluding remarks point towards future research directions, emphasizing the need to develop the integration of AI algorithms with digital twins for internal combustion engines and identify gaps for further improvements in fault diagnosis and prediction techniques.…”
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A dimension reduction assisted credit scoring method for big data with categorical features by Tatjana Miljkovic, Pei Wang

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Transformer network for time series prediction via wavelet packet decomposition by Zhichao Wu, Aiye Shi, Yan Ping Tao

“…Although, conventional time series processing methods—such as multi-scale feature extraction or Transformer-based algorithms—produce superior prediction results, when dealing with data that contain morenoise and outliers, the prediction ability of such methods can suffer. …”
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Development and validation of a CT algorithm based on intratumoral necrosis and tumor morphology to predict the nuclear grade of small (2–4 cm) solid clear cell renal cell carcinoma by Jianyi Qu, Pingyi Zhu, Xianli Zhu, Xinyan Li, Wenjie Zhang, Xinhong Song, Xiaofei Wang, Chenchen Dai, Qianqian Zhang, Jianjun Zhou

“…The study aimed to develop and validate a CT algorithm for the prediction of the WHO/ISUP nuclear grade of small (2–4 cm) solid ccRCC. …”
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Derivation and external validation of a risk prediction algorithm to estimate future risk of cardiovascular death among patients with type 2 diabetes and incident diabetic nephropathy: prospective cohort study by Bin Zhao, Jin Shang, Xiaoxue Zhang

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NoiseAugmentNet-HHO: Enhancing Histopathological Image Classification Through Noise Augmentation by Prem Purusottam Jena, Debahuti Mishra, Kaberi Das, Sashikala Mishra

Subjects: “…Noise reduction…”
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Assessing the temporal transferability of machine learning models for predicting processing pea yield and quality using Sentinel-2 and ERA5-land data by Michele Croci, Manuele Ragazzi, Alessandro Grassi, Giorgio Impollonia, Stefano Amaducci

“…This study aims to rigorously quantify this temporal transferability gap for both pea yield and TR prediction. Four ML algorithms (RF, XGBoost, GPR, SVMr) were evaluated using Sentinel-2 and ERA5-Land data from 2018 to 2024 in northern Italy. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…This study presents a comparative analysis of hyper-parameter optimization methods used in developing predictive models for patients at risk of heart failure readmission and mortality. …”
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FDR coding and decoding algorithm for reliable transmission in underwater acoustic network by Lijuan WANG, Xiujuan DU, Chong LI

“…By analyzing the shortcomings of RLT coding and decoding algorithm,a filtering dimension reduction (FDR) algorithm was proposed,which eliminated the waiting time of the traditional decoding algorithm and achieves fast decoding.In addition,XOR operation between encoded packages effectively increased the number of one-degree encoded packages,and improved decoding probability while reducing transmission delay.An optimized degree distribution function for FDR decoding algorithm was proposed,which increased the proportion of two-degree,three-degree and four-degree encoded packages,further increased the probability of one-degree packet,so that speeded up the decoding progress.Simulation results with NS3 show that the decoding success probability of FDR algorithms higher than RLT algorithm.…”
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Speech emotion recognition algorithm of intelligent robot based on ACO-SVM by Xueliang Kang

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Machine learning model for predicting in-hospital cardiac mortality among atrial fibrillation patients by Huasheng Lv, Xuehua Bi, Shuai Shang, Meng Wei, Xianhui Zhou, Kai Wang, Baopeng Tang, Yanmei Lu

“…Abstract This study developed and validated a machine learning (ML) model to predict in-hospital cardiac mortality in 18,727 atrial fibrillation (AF) patients using electronic medical record data. …”
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Point-to-Interval Prediction Method for Key Soil Property Contents Utilizing Multi-Source Spectral Data by Shuyan Liu, Dongyan Huang, Lili Fu, Shengxian Wu, Yanlei Xu, Yibing Chen, Qinglai Zhao

“…Among these strategies, the outer-product analysis fusion algorithm proved particularly effective in improving prediction accuracy. …”
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Improving T2D machine learning-based prediction accuracy with SNPs and younger age by Cynthia AL Hageh, Andreas Henschel, Hao Zhou, Jorge Zubelli, Moni Nader, Stephanie Chacar, Nantia Iakovidou, Haralampos Hatzikirou, Antoine Abchee, Siobhán O’Sullivan, Pierre A. Zalloua

“…Integration of a polygenic risk score (PRS) further supported risk prediction, particularly in younger individuals, though incremental gains were modest. …”
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Construction of a risk prediction model for occupational noise-induced hearing loss using routine blood and biochemical indicators in Shenzhen, China: a predictive modelling study by Wenting Feng, Wen Zhang, Yan Guo, Naixing Zhang, Liang Zhou, Dafeng Lin, Linlin Chen, Caiping Li, Liuwei Shi, Xiangli Yang, Peimao Li, Dianpeng Wang

“…Routine blood and biochemical indicators were extracted from the case data, and a range of machine learning algorithms including extreme gradient boosting (XGBoost) were employed to construct predictive models. …”
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A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters by Muhammad Asif, Maaz Bin Ahmad, Imtiaz A. Taj, Muhammad Tahir

“…In this paper, a generalized multi-layer framework is presented, which provides a hierarchical optimized way to select MB prediction parameters. Each layer of the proposed framework incorporates multiple innovative algorithms to shortlist the candidate prediction parameters prior to the RDO process. …”
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Early stage prediction of bone regeneration using FEA and cell differentiation algorithms with 3D-printed PLA and PCL scaffolds: modeling and application to dorsal double-plating in distal radius fractures by Hsuan Chih Liu, Ya-Han Chan, Shao-Fu Huang, Wei-Che Tsai, Yen Cheng, Chun-Li Lin

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Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical... by Hsiang-Wen Lin, Tien-Chao Lin, Chien-Ning Hsu, Tzu-Pei Yeh, Yu-Chieh Chen, Liang-Chih Liu, Chen-Yuan Lin

“…The backward LR method and seven ML algorithms were applied to train and test the prediction models. …”
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