Machine learning based on patch antenna design and optimization for 5 G applications at 28GHz by Md․Sohel Rana, Sheikh Md․ Rabiul Islam, Sanjukta Sarker

“…The efficiency of the design-I was 89.66 %, and design-II was, 52.65 %. In this paper, a predictive model was developed using a polynomial regression algorithm to create a predictive model for the designed antenna. …”
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A comparative study of bone density in elderly people measured with AI and QCT by Min Guo, Min Guo, Yu Zhang, Yu Zhang, XinXin Gu, XinXin Gu, Xuhui Liu, Xuhui Liu, Fei Peng, Fei Peng, Zongjun Zhang, Zongjun Zhang, Mei Jing, Mei Jing, Yingxia Fu, Yingxia Fu

“…The linear regression fit between the R2 values of QCT and Bone Density AI for measuring lumbar spine BMD with different equipment ranged from 0.88 to 0.96, indicating a high degree of consistency between the two measurement methods across devices.ConclusionThis multicenter study pioneers a dual-validation framework to establish the clinical validity of deep learning-based BMD prediction algorithms using routine thoracic/abdominal CT scans. …”
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Short-Term Traffic Flow Forecasting Model Based on GA-TCN by Rongji Zhang, Feng Sun, Ziwen Song, Xiaolin Wang, Yingcui Du, Shulong Dong

“…The prediction error was considered as the fitness value and the genetic algorithm was used to optimize the filters, kernel size, batch size, and dilations hyperparameters of the temporal convolutional neural network to determine the optimal fitness prediction model. …”
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Calibration Transfer of Near-Infrared Spectroscopic Model for Soluble Solid Content Predication of Apples by the Combined Use of Direct Standardization and Piecewise Direct Standar... by CHENG Ye, HUANG Haoran, WANG Ying, XIONG Zhixin

“…The results indicated that compared with DS and PDS, the combined algorithm not only significantly improved the prediction performance of the model for the slave instrument, but also mitigated the artifacts caused by PDS. …”
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Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson’s Disease by Means of Machine Learning Models by Giuseppe Cesarelli, Leandro Donisi, Francesco Amato, Maria Romano, Mario Cesarelli, Giovanni D'Addio, Alfonso M. Ponsiglione, Carlo Ricciardi

“…The investigation carried out in our work has proved the predictive power of the features, extracted from the reaching tasks involving the upper limbs, to distinguish HCs and PD patients.…”
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Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis by Xingren Liu, Junmei Song, Shujin Guo, Yi Liao, Jun Zou, Liqing Yang, Caiyu Jiang

“…Genes from this module were used to construct diagnostic and prognostic models, which demonstrated strong predictive performance across multiple validation datasets. …”
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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 CO2 Monitoring for Diagnosis of Sleep Apnea Using Neural Cryptography Techniques by Manar Ahmed Hamza, Maha M. Althobaiti, Ola Abdelgney Omer Ali, Souad Larabi-Marie-Sainte, Majdy M. Eltahir, Anwer Mustafa Hilal, Mesfer Al Duhayyim, Ishfaq Yaseen

“…The key advantage of the proposed work shows excellent performance in the prediction of adsorbing carbon and accuracy. The accuracy of the GEP-KNN algorithm with different K values produced the highest accuracy at K=9 and k=10 of 95.12% and 95.67%; the lowest accuracy is K=1 of 65.34%.…”
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A new approach to K-nearest neighbors distance metrics on sovereign country credit rating

“…The primary objective is to enhance KNN's predictive accuracy by integrating a feature importance mechanism derived from the random forest algorithm, which prioritizes significant features and reduces the impact of less relevant ones, refining the distance computation within KNN. …”
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Simultaneous determination of the amylose and amylopectin content of foxtail millet flour by hyperspectral imaging by Guoliang Wang, Min Liu, Hongtao Xue, Erhu Guo, Aiying Zhang

“…Results demonstrated that the key band extraction combined algorithm effectively reduced data dimension without compromising the accuracy of the prediction model. …”
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Russian Cross-disciplinary Consensus on the diagnosis and treatment of spondyloarthritis associated with inflammatory bowel diseases by Galina V. Lukina, Oleg V. Knyazev, Elena A. Belousova, Diana I. Abdulganieva, Elena N. Aleksandrova, Igor G. Bakulin, Olga I. Barysheva, Maria А. Borisova, Bella А. Vykova, Alla А. Godzenko, Irina V. Gubonina, Tatiana V. Dubinina, Tatiana N. Zhigalova, Evgeny V. Zhilyaev, Anna V. Kagramanova, Tatiana V. Korotaeva, Alexander V. Kuzin, Maria A. Livzan, Aleksander M. Lila, Vadim I. Mazurov, Evgeny L. Nasonov, Alexander A. Novikov, Marina F. Osipenko, Asfold I. Parfenov, Larisa V. Tarasova, Olga V. Khlynova, Marina V. Shapina, Oksana B. Shchukina, Shandor F. Erdes, Aleksei A. Iakovlev

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Comprehensive profiling of chemokine and NETosis-associated genes in sarcopenia: construction of a machine learning-based diagnostic nomogram by Yingwei Wang, Le Wang, Yan Zhang, Minghui Wang, Huaying Zhao, Cheng Huang, Huaiyang Cai, Shuangyang Mo

“…The nomogram models demonstrated high predictive accuracy in distinguishing sarcopenia from both healthy and pre-sarcopenic states, as evidenced by AUC values of 0.837 (95% CI 0.703–0.947) and 0.903 (95% CI 0.789–0.989), respectively. …”
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Application of Bivariate Reproducing Kernel-Based Best Interpolation Method in Electrical Tomography by Yongguang Tan, Jingqi Wang, Junqi Yu, Boqi Wu, Jinchao Shen, Xiangchen Guo

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Distributed consensus problem with caching on federated learning framework by Xin Yan, Yiming Qin, Xiaodong Hu, Xiaoling Xiao

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The exploration of hypertension prevention and control scheme and information construction in Qingdao by Lv Kunzheng, Zhu Yingliang, Wang Zixin, Wang Pei, Wang Han, Sun Yong, Duan Haiping, Zhang Jianjun

“…In the process of the project, our medical team and information technology team cooperated closely to develop software and algorithms, including health management system, underlying database, app and intelligent background system, which made our project have tools, challenges and output.…”
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Extended version of decision making model for industrial robot selection via fractional continuous fuzzy information by Asaf Khan, Saifullah Khan, Ariana Abdul Rahimzai, Saleem Abdullah

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Correlations between blood group and Rh factor in families and autism spectrum disorder: A comprehensive analysis by Adil Abdul-Rehman Siddiq Al-Salihy

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Immersive technologies as a component of the formation of professional competencies of students in the program "Industrial and Fire safety" by E. R. Abdulina

“…The research is based on the analysis of scientific and methodological literature on the problems of immersive education, the features of the competence approach, comparison of educational results, systematization, observation, generalization, pedagogical experiment, etc.Results and discussion. …”
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AI-driven disinformation: policy recommendations for democratic resilience by Alexander Romanishyn, Olena Malytska, Vitaliy Goncharuk

“…Recent evidence indicates that AI-enabled tools, particularly generative models and engagement-optimization algorithms, play a central role in the production and amplification of disinformation. …”
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Video Recognition of Government Community Management Cases Based on Partial Differential Equation Method by Yumeng Sun

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