A Model for Fat Content Detection in Walnuts Based on Near-Infrared Spectroscopy by Langqin Luo, Honghua Zhang, Yu Wang, Jianliang Zhang, Rui Zhang, Shan Gao, Yuanyong Dian, Zijin Bai, Chunhui Feng, Ze Zhang

“…After first optimizing the initial spectrum data using five preprocessing methods, we established separate prediction models for walnut kernel fat content based on either a back propagation neural network or a support vector regression (SVR) algorithm. …”
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Association of white matter hyperintensity burden and infarct volume in the anterior choroidal artery territory with early neurological progression: a dual-center retrospective stu... by Weiwei Gao, Weiwei Gao, Lixue Wang, Junyi Huang, Yitao Yu, Jingjing She, Jingjing She, Jingjing She, Mingyang Wang, Lijuan Cai, Lijuan Cai, Taishan Kang, Xingyu Chen, Xingyu Chen, Jianzhong Lin, Renjing Zhu, Renjing Zhu, Renjing Zhu

“…WMH burden and infarct volume were assessed using the Fazekas visual rating scale and an automated volumetric quantification method based on lesion prediction algorithm, respectively. The primary outcome was early neurological progression. …”
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Global high-resolution fire-sourced PM_2.5 concentrations for 2000–2023 by Y. Hu, C. Tian, X. Yue, Y. Lei, Y. Cao, R. Xu, Y. Guo

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Practical aspects of forecasting the company’s financial performance by V. V. Kookueva, A. A. Aliev, R. I. Khavich

“…The article considers the methodological problems of forecasting key financial indicators related to forecasting the final results of the company. The algorithm for creating refined factor predictive models of financial indicators has been presented and tested. …”
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Determining Functional Safety Indices of CWR Track Subject to Action of Thermal Compression Forces by O. A. Suslov

“…For the time being JSC RZD is well on the way from predictive track maintenance pattern to the pattern implying actual track condition analysis based planning of the quantities of maintenance work and respective expenditures. …”
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Machine learning and multi-omics analysis reveal key regulators of proneural–mesenchymal transition in glioblastoma by Can Xu, Jin Yang, Huan Xiong, Xiaoteng Cui, Yuhao Zhang, Mingjun Gao, Lei He, Qiuyue Fang, Changxi Han, Wei Liu, Yangyang Wang, Jin Zhang, Ying Yuan, Zhaomu Zeng, Ruxiang Xu

“…The TIDE algorithm was used to examine immunotherapy scores. …”
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Exploring the role of ferroptosis in pemphigus: identification of diagnostic markers and regulatory mechanisms by Jing Mao, Jianping Lan, Zheyu Zhuang, Ying Chen, Ying Chen, Yushan Ou, Xinhong Su, Xueting Zeng, Fuchen Huang, Zequn Tong, Xiaoqing Lv, Xiaoqing Lv, Xiaoqing Lv, Hui Ke, Zhenlan Wu, Ying Zou, Bo Cheng, Bo Cheng, Bo Cheng, Chao Ji, Chao Ji, Chao Ji, Ting Gong

“…Finally, experimental validation was conducted through real-time quantitative PCR, transmission electron microscopy, and drug prediction.ResultsOur results identified 1,840 DEGs in pemphigus patients compared to controls, with significant enrichment in pathways such as PI3K-Akt signaling and fatty acid metabolism. …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…To improve the interpretability of the leukemia detection process, explainable AI techniques, including Grad-CAM, Score-CAM, and Grad-CAM++, were integrated to vi-sualize critical regions influencing model predictions. These techniques enhance transparency by providing visual explanations of classification decisions. …”
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The Transformative Impact of Artificial Intelligence in Healthcare: Innovations, applications, and future prospects by Shen Ruoyu

“…This study discusses the transformative applications of AI in healthcare, including how technologies such as machine learning, neural networks, deep learning, and natural language processing can be used for diagnosis, personalized medicine, predictive analytics, virtual health assistants, surgery, and rehabilitation. …”
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Residual XGBoost regression-Based individual moving range control chart for Gross Domestic Product growth monitoring. by Rahida Rihhadatul Aisy, Latifatuz Zulfa, Yolanda Rahim, Muhammad Ahsan

“…By effectively capturing complex nonlinear relationships and mitigating autocorrelation, the proposed model offers enhanced predictive accuracy compared to conventional methods. …”
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Artificial intelligence-assisted method of structural health monitoring of subway shield tunnel based on insulation degradation location. by Yiwei Zhao, Chengtao Wang, Yi Tao

“…The present study is dedicated to develop an integrated network-based method for locating the insulation degradation in subway tunnel. In this work, a predictive model based on LWQPSO-SOM algorithm is designed to cluster the risk level of stray current leakage through data mining. …”
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Exploring Artificial Intelligence for Enhanced Endodontic Practice: Applications, Challenges, and Future Directions by Santosh R. Patil, Mohmed Isaqali Karobari

“…However, challenges such as data privacy issues, algorithmic biases, and integration barriers must be addressed to enable broader adoption. …”
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A Critical Review of the Prospect of Integrating Artificial Intelligence in Infectious Disease Diagnosis and Prognosis by Shuaibu Abdullahi Hudu, Ahmed Subeh Alshrari, Esra’a Jebreel Ibrahim Abu-Shoura, Amira Osman, Abdulgafar Olayiwola Jimoh

“…This paper reviews how AI-driven models improve diagnostic accuracy, predict patient outcomes, and contribute to effective disease management. …”
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L-Shaped-Sensor-Array-Based Localization and Tracking Method for 3D Maneuvering Target by Xing Zhang, Xue Wang

“…Thirdly an autoregressive (AR) particle filter (PF) algorithm is realized to predict the locations in the next moment. …”
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Feature selection and aggregation for antibiotic resistance GWAS in Mycobacterium tuberculosis: a comparative study by Kirill Reshetnikov, Daria Bykova, Daria Bykova, Konstantin Kuleshov, Konstantin Kuleshov, Konstantin Chukreev, Egor Guguchkin, Alexey Neverov, Gennady Fedonin

“…For some antibiotics, the resistance of a particular isolate can be reliably predicted by identifying specific mutations, while for other antibiotics the knowledge of resistance mechanisms is limited. …”
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Assessment of a Hyperspectral Remote Sensing Model Performance for Particulate Phosphorus in Optically Shallow Lake Water by Banglong Pan, Wuyiming Liu, Zhuo Diao, Qianfeng Gao, Lanlan Huang, Shaoru Feng, Juan Du, Qi Wang, Jiayi Li, Jiamei Cheng

“…This study aims to propose an algorithm to accurately predict the PP concentration and to assess the performance of the model. …”
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Nondestructive On-Site Detection of Soybean Contents Based on An Electrothermal MEMS Fourier Transform Spectrometer by Donglin Wang, Peng Wang, Huan Liu, Hongqiong Liu, Jicheng Zhang, Weiguo Liu, Huikai Xie

“…More than 300 samples of soybeans are collected, 80% of which are used to establish a prediction model using chemometrics methods. The standard error is no more than 3% when using the prediction model to test the remaining 20% samples.…”
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TCN–Transformer Spatio-Temporal Feature Decoupling and Dynamic Kernel Density Estimation for Gas Concentration Fluctuation Warning by Yanping Wang, Longcheng Zhang, Zhenguo Yan, Jun Deng, Yuxin Huang, Zhixin Qin, Yuqi Cao, Yiyang Wang

“…This study addresses the problems of multi-source data redundancy, insufficient feature capture timing, and delayed risk warning in the prediction of gas concentration in fully mechanized coal-mining operations by constructing a three-pronged technical approach that integrates feature dimensionality reduction, hybrid modeling, and intelligent early warning. …”
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Azo Dyes and the Microbial World: Synthesis, Breakdown, and Bioactivity by Valery M. Dembitsky, Alexander O. Terent’ev

“…Using mathematical algorithms and the PASS program, researchers predict new potential applications based on their structure–activity relationships. …”
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The DaTa Encryption Based on Discrete Chaotic SYSTEMS AND MAPS by A. V. Sidorenko, K. S. Mulyarchik

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