Bimodal In Situ Analyzer for Circular RNA in Extracellular Vesicles Combined with Machine Learning for Accurate Gastric Cancer Detection by Yuhang Guo, Shihua Luo, Sinian Liu, Chao Yang, Weifeng Lv, Yuxin Liang, Tingting Ji, Wenbin Li, Chunchen Liu, Xin Li, Lei Zheng, Ye Zhang

“…Most current research is focused on identifying new biomarkers and their functional significance in disease regulation. However, the practical application of EV‐circRNAs in the early diagnosis of GC is yet to be thoroughly explored due to the low accuracy of EV‐circRNAs analysis. …”
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Improvement strategies for heuristic algorithms based on machine learning and information concepts: a review of the seahorse optimization algorithm by Shixing Zheng

“…To overcome the mechanical limitations of traditional inertia weight optimization methods, this study draws inspiration from machine learning models and proposes an inertia weight optimization strategy based on the K-nearest neighbors (KNN) principle with dynamic adjustment properties. …”
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Do-Not-ResuscitateDecision-Making during the COVID-19 Pandemic in a Teaching Hospital: Lessons Learned for the Future by Mick van de Wiel, Sabrina van Ierssel, Walter Verbrugghe, Veerle Mertens, Annelies Janssens

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Predicting Urban Vitality at Regional Scales: A Deep Learning Approach to Modelling Population Density and Pedestrian Flows by Feifeng Jiang, Jun Ma

“…By advancing urban vitality prediction, UVPN provides a robust framework for evidence-based urban planning, supporting the creation of more sustainable, functional, and livable cities.…”
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Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

“…The estimation of soil organic matter (SOM) content is essential for understanding the chemical, physical, and biological functions of soil. It is also an important attribute reflecting the quality of black soil. …”
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Consumptive Water Use and Efficiency of Irrigated U.S. Corn: Learning From Hundreds of Site‐Management‐Year Observations by Meetpal S. Kukal

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Low-cost fabrication and comparative evaluation of machine learning algorithms for flexible PDMS-based hexagonal patch antenna by Srivatsan Sarvesan, Mettu Goutham Reddy, S. S. Karthikeyan, Praveen K. Sekhar

“…Additionally, a low-cost and scalable fabrication approach was demonstrated to realize conductive traces on PDMS, and a functional prototype was manufactured and tested. The prototype demonstrated consistent performance, with measured gain of 3.2 dB. …”
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The classification of absence seizures using power-to-power cross-frequency coupling analysis with a deep learning network by A.V. Medvedev, B. Lehmann

“…New artificial intelligence methods such as deep learning neural networks can provide powerful tools for automated analysis of EEG. …”
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Design language learning with artificial intelligence (AI) chatbots based on activity theory from a systematic review by Yan Li, Xinyan Zhou, Hong-biao Yin, Thomas K. F. Chiu

“…Most recent review studies overlook student learning outcomes and the methods to achieve these outcomes in chatbot-supported language learning. …”
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E-didactics design of differential calculus based on TPACK to overcome learning obstacles for mathematics pre-service teachers by Ika Meika, Nenden Suciyati Sartika, Asep Sujana, Jarinah Jarinah, Zaenal Hakim, Ika Safitri Windiarti, Hendra Hendra

“…The improvement in learning outcomes demonstrates the effectiveness of the e-didactics design: 52% in real number systems and functions, 74% in limits, 88% in derivatives, and 65% in the application of derivatives. …”
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Research on intelligent identification of microscopic substances in shale scanning electron microscope images based on deep learning theory by Ruigang Zhang, Xiangru Chen, Xin Tang, Qiuqi Chen, Sen Guo, Cheng Liu, Zhengchao Guo, Yuerong Zhou, Xiaoyi Zhou

“…The results show that the improved deep learning model performs better than other deep learning models. …”
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Physics-Informed Learning Framework for Lower Limb Kinematic Prediction With Sparse Sensors and Its Application in Chronic Stroke by Yan Guo, Yusuke Sekiguchi, Wen Zeng, Satoru Ebihara, Dai Owaki, Mitsuhiro Hayashibe

“…Accurate measurement of lower limb joint angles enables therapists to assess the functional status of stroke patients, thereby promoting the rehabilitation process. …”
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An ensemble learning approach for predicting nanoparticle dispersion properties in cutting fluids using a small sample dataset by Abhishek Shrotriya, Vinay Vakharia, Himanshu Borade, Rakesh Chaudhari, Jay Vora

“…This study examines and predicts the dispersion properties of three nanoparticles- CuO, Al2O3, and graphene when dissolved in distilled water with sodium lauryl sulfate (SLS), which functions as a nanofluid surfactant to determine its appropriateness as a cutting fluid. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…This study presents a robust forecasting framework that combines advanced feature selection techniques with deep learning architectures---namely MLP, GRU, LSTM, BiLSTM, and CNN---to enhance daily PV power prediction accuracy. …”
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A machine learning based authentication and intrusion detection scheme for IoT users anonymity preservation in fog environment. by Khondokar Oliullah, Md Whaiduzzaman, Md Julkar Nayeen Mahi, Tony Jan, Alistair Barros

“…Our proposed scheme utilizes several hash functions through symmetric encryption and decryption techniques to ensure secure end-to-end communication.…”
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Domain-Adaptive Direction of Arrival (DOA) Estimation in Complex Indoor Environments Based on Convolutional Autoencoder and Transfer Learning by Lingyu Shen, Jianfeng Li, Jingjing Pan, Junpeng Shi, Rui Xu, Hao Wang, Weiming Deng

“…The CAE-DANN enables transfer learning between data with similar features from different domains. …”
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Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations by Yong Li, Xin Sun, Yongtao Qu, Shuling Yang, Yueyi Zhai, Yan Qu

“…Abstract This study aimed to explore the combined impacts of occupational noise and dust on hearing and extra-auditory functions and identify associated risk factors via machine learning techniques. …”
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Soil Structure Analysis with Attention: A Deep-Learning-Based Method for 3D Pore Segmentation and Characterization by Italo Francyles Santos da Silva, Alan de Carvalho Araújo, João Dallyson Sousa de Almeida, Anselmo Cardoso de Paiva, Aristófanes Corrêa Silva, Deane Roehl

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Deep Learning-Based Performance Prediction of Electric Submersible Pumps Under Viscous and Gas–Liquid Flow Conditions by Haiwen Zhu, Hong Yu, Qiang Sun, Qiuchen Wang, Haorong Jing, Rakhymzhan Abdikadyrov

“…This research provides a comparative analysis of traditional curve-fitting methods, mechanistic modeling, and seven machine learning approaches. A key innovation of this study is an in-depth sensitivity analysis of different machine learning methods, especially focused on neural network parameters, such as activation functions and training configurations, to assess their impact on prediction accuracy and identify optimal network designs. …”
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Identification of aging-related biomarkers for intervertebral disc degeneration in whole blood samples based on bioinformatics and machine learning by Zi-hang Li, Shi-pian Li, Shi-pian Li, Ya-hao Li, Yu-cheng Wang, Zhen-yu Tang, Kai-yang Xu, Xiao-rong Li, Zhen Tan, Jiao-yi Pan, Jin-tao Liu, Hong Jiang, Zhi-jia Ma, Yu-xiang Dai, Yu-xiang Dai, Yu-xiang Dai, Peng-fei Yu

“…IntroductionAging is characterized by gradual structural and functional changes in the body over time, with intervertebral disc degeneration (IVDD) representing a key manifestation of spinal aging and a major contributor to low back pain (LBP).MethodsThis study utilized bioinformatics and machine learning approaches to identify aging-related biomarkers associated with IVDD in whole blood samples. …”
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