Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Bayesian causal discovery provides a principled framework for modeling observational data, generating posterior distributions that best represent the underlying structure. While recent algorithms offer efficient and accurate structure learning, integrating experiment design can further enhance predictive performance. …”
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ROBUST NUMERICAL METHODS FOR SOLVING THE poorly determined taskS OF ELECTRODYNAMICS AND NONLINEAR DYNAMICS by A. A. Kuraev, T. L. Popkova, V. V. Matveenko

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An Adaptive Evolutionary Causal Dynamic Factor Model by Qian Wei, Heng-Guo Zhang

“…Results: The experimental results show that the AcNowcasting algorithm can extract common factors that reflect macroeconomic fluctuations better, and the prediction accuracy of the AcNowcasting algorithm is more accurate than that of traditional nowcasting models. …”
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Hidden diversity in anthropophilic sand flies of the Monticola Series (Diptera, Psychodidae) by Bruno Leite Rodrigues, Alessandra Gutierrez de Oliveira, Leonardo Estevam Honorato da Silva, Thiago Vasconcelos dos Santos, Lidiane de Nazaré Carvalho de Oliveira, Felipe Dutra Rêgo, Andrey José de Andrade, Glédson Bandeira Maia, Israel de Souza Pinto, José Dilermando Andrade Filho, Eunice Aparecida Bianchi Galati

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Circadian Regulator-Mediated Molecular Subtypes Depict the Features of Tumor Microenvironment and Indicate Prognosis in Head and Neck Squamous Cell Carcinoma by Ling Aye, Zhanying Wang, Fanghua Chen, Yujun Xiong, Jiaying Zhou, Feizhen Wu, Li Hu, Dehui Wang

“…Circadian score was an independent risk factor and exhibited excellent predictive efficiency in both the training cohort from the TCGA database and the validation cohort from the GEO database. …”
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soundscape_IR: A source separation toolbox for exploring acoustic diversity in soundscapes by Yi‐Jen Sun, Shih‐Ching Yen, Tzu‐Hao Lin

“…This toolbox provides algorithms for supervised and unsupervised source separation (SS). …”
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Leveraging artificial intelligence to strengthen surgical systems in sub-Saharan Africa by Osedebamen Ralph-Okhiria, Ikhide Alonge

“…AI holds great potential throughout the surgical care pathway, from diagnosing and planning interventions via AI-based imaging and predictive algorithms to enabling more precise, minimally invasive procedures using AI-directed robotic platforms and navigation systems. …”
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Casualty Analysis of the Drivers in Traffic Accidents in Turkey: A CHAID Decision Tree Model by Zeliha Cagla Kuyumcu, Hakan Aslan, Nilufer Yurtay

“…This study aims to establish a model to predict the driver’s status (survived–injured–dead) as a result of the fatal-injury type of accident. …”
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Cyclical hybrid imputation technique for missing values in data sets by Kurban Kotan, Serdar Kırışoğlu

“…The algorithm aims to impute missing values more effectively by using row-based and column-based imputation techniques together and cyclically. …”
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Therapy and rehabilitation of women with diabetic adhesive capsulitis by Iryna Zharova, Yevhen Orlenko

“…The objectives of the developed program were: normalization of blood glucose levels, normalization of the functions of damaged limbs, reduction of pain syndrome, restoration of joint mobility, improvement of quality of life. …”
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Statistics release and privacy protection method of location big data based on deep learning by Yan YAN, Yiming CONG, Mahmood Adnan, Quanzheng SHENG

“…Aiming at the problems of the unreasonable structure and the low efficiency of the traditional statistical partition and publishing of location big data, a deep learning-based statistical partition structure prediction method and a differential publishing method were proposed to enhance the efficacy of the partition algorithm and improve the availability of the published location big data.Firstly, the two-dimensional space was intelligently partitioned and merged from the bottom to the top to construct a reasonable partition structure.Subsequently, the partition structure matrices were organized as a three-dimensional spatio-temporal sequence, and the spatio-temporal characteristics were extracted via the deep learning model in a bid to realize the prediction of the partition structure.Finally, the differential privacy budget allocation and Laplace noise addition were implemented on the prediction partition structure to realize the privacy protection of the statistical partition and publishing of location big data.Experimental comparison of the real location big data sets proves the advantages of the proposed method in improving the querying accuracy of the published location big data and the execution efficiency of the publishing algorithm.…”
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End-Point Static Control of Basic Oxygen Furnace (BOF) Steelmaking Based on Wavelet Transform Weighted Twin Support Vector Regression by Chuang Gao, Minggang Shen, Xiaoping Liu, Lidong Wang, Maoxiang Chu

“…Finally, the results of proposed prediction models show that the prediction error bound with 0.005% in carbon content and 10°C in temperature can achieve a hit rate of 92% and 96%, respectively. …”
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AFM Image Segmentation Based on Wave Growth of Local Maximum Regions with their Selection in Order of Decreasing Values by V. V. Rabtsevich, V. Y. Tsviatkou

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Evaluation Model of Low-Carbon Circular Economy Coupling Development in Forest Area Based on Radial Basis Neural Network by Chang Liu

“…In this paper, we study the radial neural network algorithm for low-carbon circular economy in forest area, design a coupled development evaluation model, study its algorithmic ideas operation mode and the update formula obtained by standard algorithm, and finally optimize the RBF neural network by particle swarm algorithm. …”
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Research on Hyperspectral Inversion of Soil Organic Carbon in Agricultural Fields of the Southern Shaanxi Mountain Area by Yunhao Han, Bin Wang, Jingyi Yang, Fang Yin, Linsen He

“…The results indicate that (1) the Spectral Space Transformation (SST) algorithm effectively eliminates environmental interference on image spectra, enhancing SOC prediction accuracy; (2) continuous wavelet transform significantly reduces data noise compared to other spectral processing methods, further improving SOC prediction accuracy; and (3) among feature band selection methods, the CARS algorithm demonstrated the best performance, achieving the highest SOC prediction accuracy when combined with the random forest model. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…Based on the SHAP values, the non-linear relationships between them are further clarified.ResultsThrough the analysis of 3 types of mental health benefits and 5 models, the LightGBM model outperforms other algorithms (such as Random Forest and XGBoost) in terms of prediction accuracy (R 2: 0.523 – 0.642), with its robustness in capturing complex feature interactions being verified. …”
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Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment by Chuanyu Ma, Chuanyu Ma, Guandu Li, Xiaohan Song, Xiaochen Qi, Tao Jiang

“…GO and KEGG pathway enrichment analyses were performed on these 103 positively correlated differentially expressed genes, and the proportion and type of tumour-infiltrating immune cells were assessed by TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL and EPIC algorithms in patients. In addition, we calculated the relevance of immunotherapy and predicted various drugs that might be used for treatment and evaluated the predictive power of survival models under multiple machine learning algorithms through the training set TCGA-PRAD versus the validation set PRAD-FR cohort. …”
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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…To screen for hub genes associated with OA, a combination of 10 machine learning algorithms and 113 algorithm compositions was integrated. …”
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Hybrid deep learning for IoT-based health monitoring with physiological event extraction by Sivanagaraju Vallabhuni, Kumar Debasis

“…Such a configuration increases the prediction accuracy by 10% more than that achieved by the individual models. …”
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Research on Mechanical Properties of Steel Tube Concrete Columns Reinforced with Steel–Basalt Hybrid Fibers Based on Experiment and Machine Learning by Bohao Zhang, Xiao Xu, Wenxiu Hao

“…On the basis of the experiments, a parametric expansion analysis of several structural parameters of the specimen was carried out by using ABAQUS finite element software, and a combined model NRBO-XGBoost, based on the Newton-Raphson optimization algorithm (NRBO), and the advanced machine learning model XGBoost was proposed for the prediction of the BSFCFST’s ultimate carrying capacity. …”
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