Dynamic Hypergraph Convolutional Networks for Hand Motion Gesture Sequence Recognition by Dong-Xing Jing, Kui Huang, Shi-Jian Liu, Zheng Zou, Chih-Yu Hsu

“…This paper introduces a novel approach to hand motion gesture recognition by integrating the Fourier transform with hypergraph convolutional networks (HGCNs). …”
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Rapid diagnosis of bacterial vaginosis using machine-learning-assisted surface-enhanced Raman spectroscopy of human vaginal fluids by Xin-Ru Wen, Jia-Wei Tang, Jie Chen, Hui-Min Chen, Muhammad Usman, Quan Yuan, Yu-Rong Tang, Yu-Dong Zhang, Hui-Jin Chen, Liang Wang

“…This study aims to develop a novel method for BV detection by integrating surface-enhanced Raman scattering (SERS) with machine learning (ML) algorithms. …”
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METTL1-driven nucleotide metabolism reprograms the immune microenvironment in hepatocellular carcinoma: a multi-omics approach for prognostic biomarker discovery by Xie Weng, Yangyue Huang, Zhuoya Fu, Xingli Liu, Fuli Xie, Jiale Wang, Qiaohua Zhu, Dayong Zheng, Dayong Zheng

“…Weighted Gene Co-expression Network Analysis (WGCNA) identified hub genes that were subsequently used to construct robust prognostic models via multiple machine learning algorithms. …”
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Comparison of Raman spectroscopy with mass spectrometry for sequence typing of Acinetobacter baumannii strains: a single-center study by Suling Liu, Ni Zhang, Jiawei Tang, Chong Chen, Weisha Wang, Jingfang Zhou, Long Ye, Xiaoli Chen, ZhengKang Li, Liang Wang

“…This study developed a novel approach, combining surface-enhanced Raman spectroscopy (SERS) with machine-learning (ML) algorithms, to construct predictive models for A. baumannii sequence typing based on SERS spectra. …”
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Semantic processing of argument structure during naturalistic story listening: Evidence from computational modeling on fMRI by Tianze Xu, Jixing Li, Xiaoming Jiang

“…The methodological framework integrated a general linear model (GLM) analysis of the fMRI data with computational modeling using natural language processing algorithms. …”
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The application of super-resolution ultrasound radiomics models in predicting the failure of conservative treatment for ectopic pregnancy by Mingyan Zhang, Junfa Sheng

“…Feature selection involved statistical testing and Least Absolute Shrinkage and Selection Operator (LASSO) regression. Random forest algorithms were used to construct NR and SR models. …”
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Sustainability Study of Community Disaster Resilience Evolution Trends Based on Dissipative Structure Theory by Weijing Liang, Ye Xue

“…This study contributes by integrating multiple models and algorithms to assess community resilience, proposing a dynamic evolutionary model, and validating its feasibility through case studies. …”
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Product Innovation Design Method Based on BP Neural Network by Shihui Huang

“…Convolutional neural network and neural style transfer model are used to extract, reconstruct, and integrate the color features of style diagrams, and transfer them to product modeling to design new product images. …”
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Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics by Zhenyu Wang, Chaojun Jiang, Xianxian Zhang, Tianchi Mu, Qingqing Li, Shu Wang, Congsong Dong, Yuan Shen, Zhenyu Dai, Fei Chen

“…Five machine learning algorithms were used to construct radiomics models (whole-brain, infarct, and combined), clinical models, and comprehensive models integrating radiomics and clinical data. …”
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Identification and validation of parthanatos-related genes in end-stage renal disease by Xuan Dai, Lianfang Yuan

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Real-time perception and intelligent early warning technology for power grid control operations based on multi-dimensional data fusion by Wei Li, Chao Hu, Bo Zhou, Weibo Peng

“…Therefore, this article proposes a real-time perception and intelligent warning technology for power grid regulation operations based on multidimensional data fusion. This technology integrates dynamic data from factories and stations, operation ticket content, and 3D virtual environment information, and uses deep learning and reinforcement learning algorithms to construct real-time perception and intelligent warning models. …”
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Molecular logic gates based on programmable self-assembly of DNA origami triangles for the detection of nucleic acid molecules by Si Sun, Jin-Da Wen, Qian-Ru Xiao, Xiao-Li Qiang, Xiao-Long Shi

“…By coupling the programmability of DNA nanostructures with molecular recognition logic, the platform constructs autonomous systems capable of interpreting biological signals via predefined algorithms. …”
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Ultrasonic Beamforming-Based Visual Localisation of Minor and Multiple Gas Leaks Using a Microelectromechanical System (MEMS) Microphone Array by Tao Wang, Jiawen Ji, Jianglong Lan, Bo Wang

“…To achieve this objective, this study integrates array signal processing and electronic techniques to construct an ultrasonic sensor array for gas leak detection and localisation. …”
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Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows by Feng Liu, Haipeng Li, Guangyuan Zou, Junlun Li

“…The AD‐based framework not only includes forword modeling and associated gradient computations for wave equations in various types of media from isotropic acoustic to vertically or horizontally transverse isotropic elastic, but also incorporates a suite of objective functions, regularization techniques, and optimization algorithms. By leveraging state‐of‐the‐art AD, objective functions such as soft dynamic time warping and Wasserstein distance, which are difficult to apply in traditional FWI are also easily integrated into ADFWI. …”
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DAFDM: A Discerning Deep Learning Model for Active Fire Detection Based on Landsat-8 Imagery by Xu Gao, Wenzhong Shi, Min Zhang, Lukang Wang

“…The proposed method outperforms other AF detection algorithms, achieving IoU and F1-score of 87.28% and 93.21%, respectively. …”
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PLOD3 as a novel oncogene in prognostic and immune infiltration risk model based on multi-machine learning in cervical cancer by Lingling Qiu, Xiuchai Qiu, Xiaoyi Yang

“…We identified 112 key metabolic genes, which were used to construct and validate a prognostic model through various machine learning algorithms. …”
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Identification of cellular senescence-associated genes for predicting the diagnosis, prognosis and immunotherapy response in lung adenocarcinoma via a 113-combination machine learn... by Ting Ge, Guixin He, Qian Cui, Shuangcui Wang, Zekun Wang, Yingying Xie, Yuanyuan Tian, Juyue Zhou, Jianchun Yu, Jinmin Hu, Wentao Li

“…A LUAD-CSRS-integrated nomogram was constructed to provide a quantitative tool for predicting prognosis in clinical practice. …”
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Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma by Xiang Li, Donghao Yin, Jiahao Geng, Yanyu Xu, Zijing Xu, Xuemeng Yang, Quanwei Li, Zimeng Shang, Zhiyun Yang, Zhong Xu, Jiabo Wang, Enxiang Zhang, Xinhua Song

“…Based on prognosis-related DEGs, patients and cells were stratified into high- and low-expression groups using corresponding computational algorithms. The intersecting DEGs from both datasets were analyzed using univariate Cox regression, and a prognostic risk score model was constructed through machine learning algorithms. …”
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Evaluation of ecological environment quality in China's mining areas by remote sensing: A review by LI Feiyue, LI Jun, XIAO Wu, ZHANG Chengye, WANG Shanshan, YANG Junquan, ZHANG Xiaoping, CHENG Yang

“…Potential research opportunities include expanding accessible indicators by remote sensing, constructing a framework for integrated data collection on the surface and underground, improving the data quality of remote sensing indicators, constructing a new indicator system for evaluation using remote sensing, and developing cloud computing algorithms.…”
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Self-supervised predictive learning accounts for cortical layer-specificity by Kevin Kermani Nejad, Paul Anastasiades, Loreen Hertäg, Rui Ponte Costa

“…Inspired by self-supervised learning algorithms, we propose a computational theory in which layer 2/3 (L2/3) integrates past sensory input, relayed via layer 4, with top-down context to predict incoming sensory stimuli. …”
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