Validation of a deep learning–based AI system for HER2-targeted breast cancer assessment using ultrasound imaging in a clinical setting by Kathryn Malherbe

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LASSO-derived nomogram prediction model for lymph node metastasis in colorectal cancer: a retrospective analysis by Xiyun Quan, Yi Deng, Zhimin Liu, Zhenqin Gao, Huimei Yi, Ming Li

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Based on the improved SCGM(1,1)c and WIV rainfall landslide susceptible area prediction model by Qian Zhang, Shujie Cao, Yanliang Du, MingYuan Du, Yixuan Zhao, Yaoqi Nie

“…On the basis of the single factor system cloud grey model (SCGM (1,1)c), an improved SCGM (1,1)c model is proposed based on Markov prediction theory and CS algorithm optimization to predict rainfall. …”
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A KNN-based model for non-invasive prediction of hemorrhagic shock severity in prehospital settings: integrating MAP, PBUCO2, PTCO2, and PPV by Peng Zhao, Wencai Pan, Xin Zou, Jiaqing Yang, Shihui Zhang, Yufei Liu, Yang Li

Subjects: “…K-nearest neighbor algorithm…”
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Post-extrasystolic variation of ST segment and T wave as a mortality risk predictor after myocardial infarction by Ralf J. Dirschinger, Ralf J. Dirschinger, Alexander Müller, Petra Barthel, Alexander Steger, Michael Dommasch, Axel Bauer, Karl-Ludwig Laugwitz, Georg Schmidt, Daniel Sinnecker, Daniel Sinnecker

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Excavating trajectory planning of electric shovel based on dynamic excavating volume prediction by Juan Wu, Rui Liu, Baoguo Lin

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Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models by Mohammad Bazrafshan, Kourosh Sayehmiri

“…A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. …”
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Reductions of GKZ systems and applications to cosmological correlators by Thomas W. Grimm, Arno Hoefnagels

“…These simpler subsystems can then be solved separately resulting in solutions for the full system. The algorithm makes it possible to check when reductions happen and allows for finding the associated simpler solutions. …”
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Geometric Degree Reduction of Wang–Ball Curves by Yusuf Fatihu Hamza, Mukhtar Fatihu Hamza, Abedallah Rababah, Salisu Ibrahim

“…In this paper, an approximate geometric multidegree reduction algorithm of Wang–Ball curves is proposed. …”
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Rolling Bearing with Isometric Feature Mapping and Fuzzy C means Fault Identification Method by WANG Ya-ping, LI Shi-song, GE Jiang-hua, XU Di, LI Yun-fei

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Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

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Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms by Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, Ana Sanches Silva, Carla Brites

“…This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric algorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). …”
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Construction and validation of a predictive model for suicidal ideation in non-psychiatric elderly inpatients by Shuyun Xiong, Dongxu Si, Meizhu Ding, Cuiying Tang, Jinling Zhu, Danni Li, Ying Lei, Lexian Huang, Xiaohua Chen, Jicai Chen

Subjects: “…Machine learning algorithms…”
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Intelligent Photolithography Corrections Using Dimensionality Reductions by Parag Parashar, Chandni Akbar, Tejender S. Rawat, Sparsh Pratik, Rajat Butola, Shih H. Chen, Yung-Sung Chang, Sirapop Nuannimnoi, Albert S. Lin

“…In this work, we use dimensionality reduction (DR) algorithms to reduce the computation time of complex OPC/EPC problems while the prediction accuracy is maintained. …”
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Sparse sufficient dimension reduction for directional regression by Gayun Kwon, Gijeong Noh, Kyongwon Kim

“…Abstract Sufficient dimension reduction has emerged as a powerful tool for extracting meaningful information within high dimensional datasets over the past few decades. …”
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A Data-Driven Strategy for Long-Term Agrarian Sustainability using the Application of Machine Learning Algorithms to Predictive Models for Pest and Disease Management by Almusawi Muntather, Ameer S. Abdul, Lalitha Yaragudipati Sri

“…PDM-MLA based on predictive modeling predicts infestations with high accuracy by analyzing weather, parameters of soil, history of outbreaks of pests, and crop health data. …”
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Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

“…The sensitivity assessment approves that the training and generalization abilities of the ELM and ANFIS models for the CS prediction of FRC are improved by their integration with the GWO algorithm. …”
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Pore size classification and prediction based on distribution of reservoir fluid volumes utilizing well logs and deep learning algorithm in a complex lithology by Hassan Bagheri, Reza Mohebian, Ali Moradzadeh, Behnia Azizzadeh Mehmandost Olya

“…Subsequently, the CUDA Deep Neural Network Long Short-Term Memory algorithm(CUDNNLSTM), belonging to the category of DL algorithms and harnessing the computational power of GPUs, is employed for the prediction of CBW, BVI, and FFV logs. …”
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Online Prediction of Concrete Temperature During the Construction of an Arch Dam Based on a Sparrow Search Algorithm–Incremental Support Vector Regression Model by Yihong Zhou, Yu Deng, Fang Wang, Chunju Zhao, Huawei Zhou, Zhipeng Liang, Lei Lei

“…First, the SSA was employed to optimize the penalty and kernel coefficients of the ISVR algorithm, minimizing errors between predicted and measured temperatures to establish a pretrained initial temperature prediction model. …”
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Using Supervised Machine Learning Algorithms to Predict Bovine Leukemia Virus Seropositivity in Florida Beef Cattle: A 10‐Year Retrospective Study by Ameer A. Megahed, Y. Reddy Bommineni, Michael Short, João H. J. Bittar

“…Objectives To compare six different supervised machine‐learning (SML) algorithms used to identify the most important risk factors for predicting BLV seropositivity in beef cattle in Florida. …”
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