Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data by Denglin Li, Luxin Zhang, Lifei Xu, Renhe Zhai, Hanyu Gao, Junlan Gao, Minghai Wei, Ningwei Che, Yeting He

“…Predictive models for OS and CSS were established based on eight machine learning algorithms, including Lasso Cox, random survival forest, CoxBoost, generalized boosted regression modelling (GBM), stepwise Cox and survival support vector machine, eXtreme Gradient Boosting, supervised principal component and partial least squares regression for Cox, and the selected predictive models were evaluated by the area under the ROC curves (AUC) and 95% confidence interval (CI), calibration curves and decision curve analyses in the training set, validation set and test set. …”
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Addressing uncertainty in identifying pregnancies in the English CPRD GOLD Pregnancy Register: a methodological study using a worked example by Yangmei Li, Jennifer J Kurinczuk, Fiona Alderdice, Maria A Quigley, Oliver Rivero-Arias, Julia Sanders, Sara Kenyon, Dimitrios Siassakos, Nikesh Parekh, Suresha De Almeida, Claire Carson

“…We compared characteristics and outcomes across these populations, examining potential biases in effect estimates using the 'as provided' population. Results Our algorithm added 22,270 (~7%) pregnancies from hospital data to the CPRD PR (1997-2021), eliminated conflicting pregnancies and pregnancies with unknown outcomes, and minimised potentially non-contemporaneous records of past pregnancies or partial records of pregnancies. …”
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A Distributed Detection Method for Quality-related Faults in Complex Non-stationary Industrial Processes by Jie DONG, Daye LI, Yanmei WEI, Kaixiang PENG, Hui YANG

“…Process variables highly correlated with quality variables are selected using the mRMR algorithm. Simultaneously, the algorithm eliminates redundancy among the selected process variables to simplify the subsequent construction of the fault detection model, enhancing its accuracy. …”
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Mapping recent timber harvest activity in a temperate forest using single date airborne LiDAR surveys and machine learning: lessons for conservation planning by G. Burch Fisher, Andrew J. Elmore, Matthew C. Fitzpatrick, Darin J. McNeil, Jeff W. Atkins, Jeffery L. Larkin

“…In this paper, we develop a timber harvest mapping workflow using machine learning (XGBoost algorithm) and single campaign airborne light detection and ranging (LiDAR) surveys for the state of Pennsylvania, USA. …”
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A stratified therapeutic model incorporated with studies on regulatory B cells for elderly patients with newly diagnosed multiple myeloma by Wenjiao Tang, Yan Li, Zhongqing Zou, Jian Cui, Fangfang Wang, Yuhuan Zheng, Li Hou, Ling Pan, Bing Xiang, Hong Chang, Li Zhang, Ting Niu

“…The proportions of patients achieving very good partial response or better were comparable among Bd, Bd + X, and Rd groups (41.9% vs. 54.5% vs. 44.0%, p = 0.472). …”
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Modern methods for adhesive bowel obstruction diagnosis by K. D. Rybakov, G. S. Sednev, E. M. Askerov, A. M. Morozov, A. N. Pichugova, M. A. Belyak

“…However, clinical symptoms are only partially able to diagnose adhesive intestinal obstruction. …”
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Tanshinone Content Prediction and Geographical Origin Classification of <i>Salvia miltiorrhiza</i> by Combining Hyperspectral Imaging with Chemometrics by Yaoyao Dai, Binbin Yan, Feng Xiong, Ruibin Bai, Siman Wang, Lanping Guo, Jian Yang

“…Finally, effective wavelengths were selected using the successive projections algorithm (SPA) and variable iterative space shrinkage approach (VISSA). …”
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Addition of punishments by V. M. Stepashin

“…The final punishment for two types of plurality - the totality of crimes and sentences – is determined by the rules of Articles 69-72 of the Criminal Code, which establishes: (a) a method for determining the final punishment (absorption, full or partial addition); (b) a basic algorithm for determining the final penalty when adding punishments imposed for individual crimes; (c) differentiated limits of the final punishment.Rules for adding punishments. …”
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Rapid and Accurate Measurement of Major Soybean Components Using Near-Infrared Spectroscopy by Chenxiao Li, Jiatong Yu, Sheng Wang, Qinglong Zhao, Qian Song, Yanlei Xu

“…Feature selection was conducted using competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), and uninformative variable elimination (UVE), followed by model construction with partial least squares regression (PLSR), support vector regression (SVR), and random forest (RF). …”
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Predicting the Traffic Crashes of Taxi Drivers by Applying the Non-Linear Learning of ANFIS-PSO with M5 Model Tree by E. Abbasi, M. Hadji Hosseinlou

“…Moreover, the linear relationships generated by M5 tree show the sensitivity of ensembled model accuracy on the single ANFIS models, which have a partial tendency in underestimation of the traffic crashes.…”
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Hyperspectral imaging combined with machine learning for high‐throughput phenotyping in winter wheat by Sehijpreet Kaur, Vijaya Gopal Kakani, Brett Carver, Diego Jarquin, Aditya Singh

“…However, combining these indices with the RF and PLSR algorithm significantly enhances the prediction accuracy. …”
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Double Stage Transfer Learning for Brain&#x2013;Computer Interfaces by Yunyuan Gao, Mengting Li, Yun Peng, Feng Fang, Yingchun Zhang

“…Some existing EEG-based TL algorithms cannot achieve good results because they only extract partial features. …”
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Knowledge Extraction via Machine Learning Guides a Topology‐Based Permeability Prediction Model by Jia Zhang, Gang Ma, Zhibing Yang, Jiangzhou Mei, Daren Zhang, Wei Zhou, Xiaolin Chang

“…We first establish an ML model between permeability and the geometry‐topology characteristics of porous media using Extreme Gradient Boosting (XGBoost) algorithm. The data set used to fit ML model is prepared from 458 samples of different types of porous media. …”
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Performance Statistics of Autoregressive Short and Ultrashort Signal Detectors by V. M. Kutuzov, V. P. Ipatov, S. S. Sokolov

“…Statistical computer simulation of the detection algorithms under consideration was conducted. This method is widely used in the analysis of parametric methods of signal processing. …”
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Improved YOLOv5s With Coordinate Attention for Small and Dense Object Detection From Optical Remote Sensing Images by Qinggang Wu, Yonglei Wu, Yang Li, Wei Huang

“…Experimental results on the NWPU VHR-10 dataset demonstrate that the proposed YOLOv5s method performs well compared with state-of-the-art algorithms.…”
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Modeling and optimizing the atmospheric water harvesting System: Application of PAN-PDMS polymeric membrane by Sepehr Sanaye, Pouya Rezvani Gil Kalaee, Javad Mahmoudimehr

“…Polymeric membranes Polydimethylsiloxane (PDMS) and polyacrylonitrile (PAN), helped to separate water vapor from air by increasing the partial pressure of water vapor on the permeate side due to the separation process. …”
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Study on adaptive multiscale finite element method for two-dimensional singularly perturbed problems with two parameters(二维双参数奇异摄动问题的自适应多尺度有限元法探究)... by 孙美玲(SUN Meiling), 陈璐(CHEN Lu), 江山(JIANG Shan)

“…This paper addresses the two-dimensional singularly perturbed partial differentiable equation with two parameters, since the existence of two scaled small parameters it would bring jumps and large errors of the solution. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…Aerial devices with limited communication and computation resource can offload partial nonprivacy data samples to proximity D2D pair, which can assist to train FL models. …”
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Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach by Gideon Addo, Bismark Amponsah Yeboah, Michael Obuobi, Raphael Doh-Nani, Seidu Mohammed, David Kojo Amakye

“…Symptoms like polyuria, polydipsia, weakness, sudden weight loss, partial paresis, polyphagia, and visual blurring were significantly associated with diabetes. …”
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Novel FTLRNN with Gamma Memory for Short-Term and Long-Term Predictions of Chaotic Time Series by Sanjay L. Badjate, Sanjay V. Dudul

“…The standard back-propagation algorithm with momentum term has been used for both the models.…”
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