Unraveling shared diagnostic genes and cellular microenvironmental changes in endometriosis and recurrent implantation failure through multi-omics analysis by Dongxu Qin, Yongquan Zheng, Libo Wang, Zhenyi Lin, Yao Yao, Weidong Fei, Caihong Zheng

“…Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify key genes. Machine learning algorithms, including Random Forest (RF) and XGBoost, were utilized to screen for shared diagnostic genes, which were subsequently validated through receiver operating characteristic (ROC) analysis and clinical prediction models. …”
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Relationships Between Oat Phenotypes and UAV Multispectral Imagery Under Different Water Deficit Conditions by Structural Equation Modelling by Yayang Feng, Guoshuai Wang, Jun Wang, Hexiang Zheng, Xiangyang Miao, Xiulu Sun, Peng Li, Yan Li, Yanhui Jia

“…However, the prediction accuracy for moisture conditions using spectral data alone is low. …”
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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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Construction and demolition waste material library based on vision systems dataZenodo by Maria Teresa Calcagni, Giovanni Salerno, Gloria Cosoli, Giuseppe Pandarese, Gian Marco Revel

“…In addition, the benefits of this resource for the scientific and industrial community are discussed, including the possibility of using the data to develop/fine-tune artificial intelligence (AI) algorithms capable of optimising sorting and recycling processes by recognition and discrimination among different types of CDW material using the aforementioned sensors. …”
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Effects of missing data imputation methods on univariate blood pressure time series data analysis and forecasting with ARIMA and LSTM by Nicholas Niako, Jesus D. Melgarejo, Gladys E. Maestre, Kristina P. Vatcheva

“…Results All imputation techniques either increased or decreased the data autocorrelation and with this affected the forecasting performance of the ARIMA and LSTM algorithms. The best imputation technique did not guarantee better predictions obtained on the imputed data. …”
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METTL1-driven nucleotide metabolism reprograms the immune microenvironment in hepatocellular carcinoma: a multi-omics approach for prognostic biomarker discovery by Xie Weng, Yangyue Huang, Zhuoya Fu, Xingli Liu, Fuli Xie, Jiale Wang, Qiaohua Zhu, Dayong Zheng, Dayong Zheng

“…Moreover, the prognostic model integrating METTL1 expression and immune checkpoint profiles shows strong predictive performance across independent cohorts, highlighting its potential clinical utility.ConclusionThis study highlights the innovative role of METTL1-driven nucleotide metabolism reprogramming in reshaping the immune microenvironment of HCC. …”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…Then, an efficient deep learning method was proposed based on this dataset to enhance the predictive performance.ResultsThe prediction accuracy achieved for the yellowing degree, browning degree, and drying degree were 83.0%, 90.5%, and 75.6% respectively. …”
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Factors influencing the response to periodontal therapy in patients with diabetes: post hoc analysis of a randomized clinical trial using machine learning by Nidia CASTRO DOS SANTOS, Arthur MANGUSSI, Tiago RIBEIRO, Rafael Nascimento de Brito SILVA, Mauro Pedrine SANTAMARIA, Magda FERES, Thomas VAN DYKE, Ana Carolina LORENA

“…We tested seven different algorithms: K-Nearest Neighbors, Decision Tree, Support Vector Machine, Random Forest, Extreme Gradient Boosting, and Logistic Regression. …”
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C2 pars interarticularis length on the side of high-riding vertebral artery with implications for pars screw insertion by Tomasz Klepinowski, Miszela Kałachurska, Michał Chylewski, Natalia Żyłka, Dominik Taterra, Kajetan Łątka, Bartłomiej Pala, Wojciech Poncyljusz, Leszek Sagan

“…Sample size was estimated with pwr package and C2PIL was measured. Cut-off value and predictive statistics of C2PIL for HRVA were computed with cutpointr package. …”
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Recommendations for All-Round Newborns and Infants Hearing Screening in Russian Federation by S. S. Chibisova, G. S. Tufatulin, L. S. Namazova-Baranova, I. V. Koroleva, E. R. Tsygankova, T. G. Markova, N. N. Volodin, G. A. Tavartkiladze

“…Maintenance of all-round newborns hearing screening algorithm will allow us to avoid the diagnosis delay, to start the rehabilitation earlier and further to significantly increase the efficacy of modern high-tech methods for correcting hearing disorders in children. …”
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Simulation of bird’s symbiocenosis by A. M. Aramisov, M. K. Kozhokov, M. M. Shahmurzov, B. K. Laypanov, M. A. Koshokova, A. G. Bulatova

“…Logical-information modeling is not fully being implemented for the prediction of possible violations of the living ecosystems. …”
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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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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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AI-Driven Particulate Matter Estimation Using Urban CCTV: A Comparative Analysis Under Various Experimental Conditions by Woochul Choi, Hongki Sung, Kyusoo Chong

“…All four experiments that excluded the nighttime, added the solar incidence angle variable, applied the distribution of PM per class, and removed the outlier removal algorithm showed high predictive power. In particular, the final experiment that satisfied all conditions, including the exclusion of nighttime, addition of solar incidence angle variable, and application of outlier removal algorithm, derived predictive values that are expected to be commercialized.…”
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Energy efficient and robust node localization in WSNs using LSTM optimized DV hop framework to mitigate multihop localization errors by Amjad Rehman, Tariq Mahmood, Tahani Jaser Alahmadi, Ahmed S. Almasoud, Tanzila Saba

“…The algorithm processes original data through filtering, analysis, and feature extraction to improve predicted node positions. …”
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A Battery Electric Vehicle Transportation Network Design Model with Bounded Rational Travelers by Xu Xin, Tao Zhang, Cui Li, Yanran Liu, Lingyu Gao, Yuchuan Du

“…With governments worldwide emphasizing environmental protection and the global focus on carbon reduction, the battery electric vehicle (BEV) industry has developed rapidly. …”
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Machine learning approaches for grain seed quality assessment: a comparative study of maize seed samples in Malawi by Wisdom Richard Mgomezulu, Moses M. N. Chitete, Beston B. Maonga, Mthakati A. R. Phiri

“…Abstract The study assessed machine and deep learning algorithms’ ability to predict and classify the quality of maize grain seed for increased agricultural output. …”
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Deep Learning Methods and UAV Technologies for Crop Disease Detection by S. G. Mudarisov, I. R. Miftakhov

“…The paper underscores the significant advancements in plant disease diagnostics achieved through the integration of remote sensing technologies and deep learning algorithms, particularly in aerial imagery interpretation. …”
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Anxiety-depressive syndrome in patients with arterial hypertension and chronic obstructive pulmonary disease with frequent exaccations by L. A. Shpagina, I. S. Shpagin, L. D. Khidirova, A. A. Vasilenko

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Current status and prospects of artificial intelligence in the diagnosis and treatment of bladder tumors by GAN Xiya, WEI Wei

“…Machine learning and deep learning algorithms have played an important role in the imaging detection and diagnosis of bladder tumors, providing high accuracy in tumor detection, grading, and staging predictions. …”
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