A Machine Learning-Based Diagnostic Nomogram for Moyamoya Disease: The Validation of Hypoxia-Immune Gene Signatures by Cunxin Tan, Xilong Wang, Zhenyu Zhou, Yutong Liu, Shihao He, Yuanli Zhao

“…These genes were further refined through machine learning algorithms. The diagnostic value was confirmed using an external dataset, and a diagnostic nomogram was constructed. …”
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Establishment and validation of an immune-related nomogram for the prognosis of pancreatic adenocarcinoma by Kan Wang, Yunkun Lu, Yanfei Cao, Ping Feng, Qiu Wu, Peng Xiao, Yimin Ding

“…This study aims to improve prognosis prediction to guide therapeutic decision-making, and to identify novel targets for immunotherapy of PDAC. …”
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Features of training 3d computer modeling and visualization of future teachers of informatics by O. G. Rylova

“…Questions on three-dimensional computer modeling and visualization will pass through the content line through the content of six academic disciplines («Computer graphics and multimedia», «Computational methods and computer modeling», «Programming Technologies and Algorithmization Methods», «Information Technologies in Education», «Methods teaching informatics» and «Architecture and software of computer systems»). …”
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A Novel Adaptive Active Disturbance Rejection Control Strategy to Improve the Stability and Robustness for a Wind Turbine Using a Doubly Fed Induction Generator by Hammadi Laghridat, Ahmed Essadki, Maha Annoukoubi, Tamou Nasser

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Design of intelligent optimization of sports strategy and training decision support system based on deep reinforcement learning by Hua Xu, Bing Lin, Long Liu

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Voltage unbalance assessment in a distribution system incorporated with renewable‐based sources and electric vehicles in an uncertain environment by Nandini K. K., Jayalakshmi N. Sabhahit, Vinay Kumar Jadoun

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A Pythagorean fuzzy MCDM model for evaluating career happiness in sports by selecting a suitable sport by JiaYan Zhu, Zeng Jiao

“…As the importance of physical education and traditional sports in promoting complete development continues to increase, the need for systematic strategies becomes paramount. …”
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Transformer Fault Diagnosis Based on Knowledge Distillation and Residual Convolutional Neural Networks by Haikun Shang, Yanlei Wei, Shen Zhang

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Multigoal-oriented a posteriori error control for heated material processing using a generalized Boussinesq model by Beuchler, Sven, Endtmayer, Bernhard, Lankeit, Johannes, Wick, Thomas

“…Therein, error reductions and effectivity indices are consulted to establish the robustness and efficiency of our framework.…”
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Development of Recurrent Neural Networks for Thermal/Electrical Analysis of Non-Residential Buildings Based on Energy Consumptions Data by Elisa Belloni, Flavia Forconi, Gabriele Maria Lozito, Martina Palermo, Michele Quercio, Francesco Riganti Fulginei

“…Simplifying input variables can enhance the applicability of artificial intelligence techniques in predicting energy and thermal performance. This study proposes a neural network-based approach to characterize the thermal–energy relationship in commercial buildings, aiming to provide an efficient and scalable solution for performance prediction. …”
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Snow Depth Extraction From Time‐Lapse Imagery Using a Keypoint Deep Learning Model by C. M. Breen, W. R. Currier, C. Vuyovich, Z. Miao, L. R. Prugh

“…At 20 snow pole locations from Grand Mesa, CO (n = 9,722 images), our model successfully predicts the top and bottom of the pole with a mean absolute error (MAE) of 1.30 cm. …”
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Imaging-based machine learning to evaluate the severity of ischemic stroke in the middle cerebral artery territory by Gang Xie, Jin Gao, Jian Liu, Xuwei Zhou, Zhengkai Zhao, Wuli Tang, Yue Zhang, Lingfeng Zhang, Kang Li

“…This algorithm was then used to construct a imaging-based prediction model for stroke severity (severe and non-severe). …”
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Detection of the Pigment Distribution of Stacked Matcha During Processing Based on Hyperspectral Imaging Technology by Qinghai He, Zhiyuan Liu, Xiaoli Li, Yong He, Zhi Lin

“…Firstly, a quantitative relationship between HSI data of tea and their pigment contents was developed based on regression analysis, and the results showed that exceptional prediction performance was achieved by the partial least squares regression (PLSR) algorithm combined with the feature band algorithm of competitive adaptive reweighting (CARS), and the R_p² values of detection models of chlorophyll a, chlorophyll b and carotenoids were 0.90465, 0.92068 and 0.62666, respectively. …”
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Identification of a Hypoxia-Angiogenesis lncRNA Signature Participating in Immunosuppression in Gastric Cancer by Zicheng Wang, Xisong Liang, Hao Zhang, Zeyu Wang, Xun Zhang, Ziyu Dai, Zaoqu Liu, Jian Zhang, Peng Luo, Jiarong Li, Quan Cheng

“…As a result, we found that HARM predicted patient survival with high accuracy and was correlated with higher stages of gastric cancer. …”
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SIGNIFICANCE OF LABORATORY PARAMETERS IN PROGNOSIS OF OUTCOMES OF ACUTE MYOCARDIAL INFARCTION by I. E. Belaya, V. I. Kolomiets, E. K. Musaeva

“…Using decision tree algorithms, we singled out laboratory parameters (attributes) which were subsequently used as input. …”
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Determination of Pear Cultivars (Pyrus communis L.) Based on Colour Change Levels by Using Data Mining by Dilara Gerdan, Abdullah Beyaz, Mustafa Vatandaş

“…The relationship between fruit hardness and colour change were also demonstrated. The predictions were done supervised machine learning algorithms (Decision Tree and Neural Networks with Meta-Learning Techniques; Majority Voting and Random Forest) by using KNIME Analytics software. …”
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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

“…Hybridising the Random-Forest algorithm with Dingo optimisation and called Regulated Random Forest (RRF) to precisely identify defect clusters and then predict the welding defect growth rate (<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {{R}_{s}}$ </tex-math></inline-formula>) using the Cat-boost optimiser, which is enhanced by a beetle search mechanism called CatBAS. …”
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Metabolic profile changes in patients with rheumatoid arthritis detected using mass spectrometry by Xue Wu, Qi Yang, Shanshan Liu, Peng Yang, Zhengqi Liu, Zhitu Zhu

“…However, the etiology of RA is still unclear, and novel biomarkers are demanded for the early prediction and diagnosis of RA and dissecting disease mechanisms. …”
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The role of FOXK2–FBXO32 in breast cancer tumorigenesis: Insights into ribosome‐associated pathways by Fuben Liao, Jinjin Zhu, Junju He, Zheming Liu, Yi Yao, Qibin Song

“…Method FOXK2 genes were analyzed using single‐cell sequencing in pan‐cancer bulk RNA‐seq from the TCGA database. We used algorithms to predict their immune infiltration. Functional enrichment and ChIP‐seq identified potential downstream gene, FBXO32. …”
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Design and validation of a novel multiple sites signal acquisition and analysis system based on pressure stimulation for human cardiovascular information by Gaiqin Liu, Yuan Li, Longcong Chen, Juan Jiang, Jie Tian, Panpan Feng

“…Furthermore, the results suggest that the system can facilitate in-depth research into the relationships between collected signals and CVDs, provide rich raw data for cardiovascular health assessment and disease prediction models based on machine learning algorithms, and offer a new non-invasive method for early diagnosis, evaluation, and prediction of CVDs.…”
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