Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…Linear discriminant analysis (LDA) discerns among transfer to haemodialysis or death, predicts whether the cause of PD end is ultrafiltration failure (UFF) or cardiovascular disease (CVD) and anticipates the type of CVD (receiver operating characteristic curve under the area>0.71).Discussion Our combination of longitudinal PD datasets, attribute shrinkage and gold-standard algorithms with overfitting testing and class imbalance ensures robust predictions in PD. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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Monte Carlo method for determination and analysis damage to the power system by D. E. Marmysh, U. I. Babaed

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MACAW: a method for semi-automatic detection of errors in genome-scale metabolic models by Devlin C. Moyer, Justin Reimertz, Daniel Segrè, Juan I. Fuxman Bass

“…Abstract Genome-scale metabolic models (GSMMs) are used to predict metabolic fluxes, with applications ranging from identifying novel drug targets to engineering microbial metabolism. …”
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Machine learning approaches for modelling of molecular polarizability in gold nanoclusters by Abhishek Ojha, Satya S. Bulusu, Arup Banerjee

“…Our results demonstrate the efficacy of machine-learning in accurately predicting the polarizability of gold nanoclusters. …”
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Method for long-term coherent-noncoherent signal accumulation with non-zero higher derivatives range to radar target by S. V. Kozlov, Van Cuong Le

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VIRTUAL TRAJECTORY MODELING by A. A. Dyatko, S. M. Kostromitski, P. N. Shumski

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Using random forests to forecast daily extreme sea level occurrences at the Baltic Coast by K. Bellinghausen, B. Hünicke, E. Zorita

“…<p>We have designed a machine learning method to predict the occurrence of daily extreme sea level at the Baltic Sea coast with lead times of a few days. …”
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Application of Wireless Sensor Networks for Indoor Temperature Regulation by Biljana Risteska Stojkoska, Andrijana Popovska Avramova, Periklis Chatzimisios

“…In this paper we focus on a system used for temperature regulation for residential, educational, industrial, and commercial premises, and so forth. …”
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A Monocyte-Driven Prognostic Model for Multiple Myeloma: Multi-Omics and Machine Learning Insights by Xie L, Gao M, Tan S, Zhou Y, Liu J, Wang L, Li X

“…Subsequently, based on 482 prognostic moDEGs, we developed and validated an optimal model, termed the Monocyte-related Gene Prognostic Signature (MGPS), by integrating 101 predictive models generated from 10 machine learning algorithms across multiple transcriptome sequencing datasets. …”
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Transcriptomics-based exploration of ubiquitination-related biomarkers and potential molecular mechanisms in laryngeal squamous cell carcinoma by Qiu Chen, Zhimin Wu, Yifei Ma

“…Meanwhile, the drugs garcinol, cocaine, and triazolam, among others, used for LSCC treatment were predicted. Finally, transcription factors (TFs) (BRD4, MYC, AR, and CTCF) were predicted to regulate the biomarkers. …”
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Simultaneous Instance and Attribute Selection for Noise Filtering by Yenny Villuendas-Rey, Claudia C. Tusell-Rey, Oscar Camacho-Nieto

“…Removing or reducing noise can help classification algorithms focus on relevant patterns, preventing them from being affected by irrelevant or incorrect information. …”
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Enhancing accuracy through ensemble based machine learning for intrusion detection and privacy preservation over the network of smart cities by Mudita Uppal, Yonis Gulzar, Deepali Gupta, Jayant Uppal, Mukesh Kumar, Shilpa Saini

“…The dataset utilized for anomaly-based detection techniques is KDDCup99 dataset, on which the different algorithms have been applied. The goal is to gain knowledge about data integrity and improve the predictive power of data. …”
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AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices by Aiswarya Baburaj, Syamini Jayadevan, Akshaya Kumar Aliyana, Naveen Kumar SK, George K Stylios

“…This review explores the synergistic potential of AI‐driven TENG systems, from optimizing materials and fabrication to embedding machine learning and deep learning algorithms for intelligent real‐time sensing. These advancements enable improved energy harvesting, predictive maintenance, and dynamic performance optimization, making TENGs more practical across industries. …”
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Research on Road Traffic Safety Risk Assessment Based on the Data of Radar Video Integrated Sensors by Xiaoyu CAI, Zimu LI, Wufeng QIAO, Xiling CHENG, Bo PENG, Dong ZHANG

“…To accurately prevent and warn of traffic accidents, this article proposes a method for predicting urban road traffic safety risks based on vehicle driving behaviour data and information entropy theory. …”
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Hybrid model for wind power estimation based on BIGRU network and error discrimination‐correction by Yalong Li, Ye Jin, Yangqing Dan, Wenting Zha

“…Abstract Accurate estimation of wind power is essential for predicting and maintaining the power balance in the power system. …”
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New non-primitive codes formed from primitive BCH and Hamming codes and their norm evaluation by V. K. Konopelko, V. A. Lipnitski

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Quality assessment of chicken using machine learning and electronic nose by Hassan Anwar, Talha Anwar

“…This study investigates the use of an electronic nose system—a sensor array that detects odors and generates data, which is then analyzed by machine learning algorithms to predict chicken freshness. An electronic nose system was developed using six MQ gas sensors and one humidity temperature sensor. …”
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Application of Machine Learning for Target Selection and Acid Treatment Design by I. I. Mannanov, M. A. Varfolomeev, G. R. Ganieva, A. R. Gimaeva, R. R. Giniyatullin

“…These algorithms significantly simplify the tasks of acid treatment design.…”
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Short-Term Electrical Load Forecasting in Power Systems Using Deep Learning Techniques by Nihat Pamuk

“…Using a real dataset for one-step forecasting, this article compares three deep learning algorithms for short-term power load forecasting: LSTM, GRUs, and CNN. …”
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