Consensus artificial intelligence-driven prognostic signature for predicting the prognosis of hepatocellular carcinoma: a multi-center and large-scale study by Wen Wen, Rui Wang

“…This study developed a consensus artificial intelligence-derived prognostic signature (CAIPS) by integrating ten machine learning algorithms (101 methods) across six multi-center HCC cohorts (n = 1110). …”
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Equivariant learning leveraging geometric invariances in 3D molecular conformers for accurate prediction of quantum chemical properties by Jianhua Sun, Ye Cao, Huijing Hu, Baoqiao Qi

“…In this study, we present a computational framework termed 3D molecular structure enhanced (3DMSE) that seamlessly integrates the rich structural information inherent in 3D molecular geometries with state-of-the-art machine learning algorithms to enable highly precise and computationally efficient prediction of crucial quantum chemical properties. …”
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Oriented ice eddy detection network based on the Sentinel-1 dual-polarization data by Jinqun Wu, Jinqun Wu, Yiqin Zheng, Tingting Wang, Chunyong Ma, Chunyong Ma, Ge Chen, Ge Chen

“…Firstly, a high-quality RGB false-color imaging method was developed based on Sentinel-1 dual-polarization (HH+HV) Extra-Wide Swath (EW) mode products, effectively integrating denoising algorithms and image processing techniques. …”
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Developing a Unified Framework for PMSM Speed Regulation: Active Disturbance Rejection Control via Generalized PI Control by Huanzhi Wang, Yuefei Zuo, Chenhao Zhao, Christopher H. T. Lee

“…With the growing demand for advanced control algorithms in permanent magnet synchronous motor (PMSM) speed regulation, active disturbance rejection control (ADRC) has garnered significant attention for its simplicity and effectiveness as an alternative to traditional proportional-integral (PI) controllers. …”
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Research on load frequency control system attack detection method based on multi-model fusion by Feng Zheng, Weixun Li, Huifeng Li, Libo Yang, Zengjie Sun

“…A multi-model fusion attack detection framework is proposed, integrating (Long Short-Term Memory) LSTM supervised learning and autoencoder unsupervised learning algorithms, with an adaptive weight adjustment mechanism that dynamically optimizes detection strategies. …”
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Development and validation of an interpretable machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients. by Chaoqun Huang, Shangzhi Shu, Miaomiao Zhou, Zhenming Sun, Shuyan Li

“…This study aimed to construct and validate an interpretable predictive model of LAT/SEC risk in NVAF patients using machine learning (ML) methods.…”
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M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy by Nalini Schaduangrat, Hathaichanok Chuntakaruk, Thanyada Rungrotmongkol, Pakpoom Mookdarsanit, Watshara Shoombuatong

“…Using these balanced subsets, we explored and evaluated heterogeneous base-classifiers trained with a variety of SMILES-based feature descriptors coupled with popular ML algorithms. Finally, M3S-GRPred was constructed by integrating probabilistic feature from the selected base-classifiers derived from a two-step feature selection technique. …”
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An MRI-based fusion model for preoperative prediction of perineural invasion status in patients with intrahepatic cholangiocarcinoma by Zuochao Qi, Hao Yuan, Qingshan Li, Pengyu Chen, Dongxiao Li, Kunlun Chen, Bo Meng, Peigang Ning, Haibo Yu, Deyu Li

“…Feature selection was performed, and a radiomics model was constructed using machine learning algorithms, followed by SHapley Additive exPlanations (SHAP) visualization. …”
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Development of a machine learning-derived dendritic cell signature for prognostic stratification in lung adenocarcinoma by Fang Zhou, Fang Zhou, Meng Wang, Meng Wang, Zheng Wang, Zheng Wang, Wei Li, Wei Li, Xike Lu, Xike Lu

“…A dendritic cell-related signature (DCRS) was constructed using multiple machine learning algorithms (Lasso-Cox, RSF, CoxBoost, Stepwise-Cox), and its prognostic performance was validated in seven external cohorts. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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Plot-Rice v1.0: A global plot-based rice benchmark dataset with spatiotemporal heterogeneity for scientific deep learning by Ji Ge, Hong Zhang, Wenjiang Huang, Zihuan Guo, Lu Xu, Yazhe Xie, Mingyang Song, Yinhaibin Ding, Chao Wang

“…In terms of feature composition, Plot-Rice integrates multi-source features, including radar backscattering coefficients, normalized backscattering coefficients, radar vegetation indices, spectral indices, and spectral combinations, constructing time series for 12 months of 2023 to facilitate temporal analysis. …”
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Design of a Heterogeneous-Based Network Intrusion Detection System and Compiler by Zhigui Lin, Xiaofeng Zhang, Qi Liu, Jun Cui

“…This paper is based on the collaborative design consept of “hardware-accelerated preprocessing + software-based precise detection”, fully leveraging FPGA’s parallel processing capabilities and CPU’s flexible computation advantages. We construct an FPGA + CPU heterogeneous detection system featuring a five-tuple segmented matching architecture, which integrates hash bitmap and shift-or algorithms to achieve fast-pattern matching. …”
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River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network by Ling Gao, Zhen Zhang, Lin Chen, Huabao Li

“…However, environmental interference often blurs weak tracer textures in STIs, limiting the accuracy of traditional MOT detection algorithms based on shallow features like images’ gray gradient. …”
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AI-Based Linguistic Frameworks for Monitoring Physical Health, Sports Performance, and Educational Contexts by Rakhimov Vladimir, Saidnazarov Ulugbek, Mustafaev Ispandiyar

“…Rather, their perceptual feedback loops and adaptive interpretations are integrated into the iterative refinement of monitoring algorithms. …”
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Identification of stemness subtypes and prognostic modeling in thyroid cancer: the critical role of DPYSL3 in tumor progression and immune microenvironment by Jialong Yu, Wei Luo, Guangwei Xu, Mei Tao, Yuqi Wang, Qiman Dong, Linfei Hu, Xiukun Hou, Jingzhu Zhao, Dapeng Li, Songfeng Wei, Xianhui Ruan, Xiangqian Zheng

“…Through the application of four machine learning algorithms and LASSO regression, we identified key genes and constructed a prognostic model based on the stemness signature. …”
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SpectralEarth: Training Hyperspectral Foundation Models at Scale by Nassim Ait Ali Braham, Conrad M. Albrecht, Julien Mairal, Jocelyn Chanussot, Yi Wang, Xiao Xiang Zhu

“…Utilizing state-of-the-art self-supervised learning algorithms, we pretrain a series of foundation models on SpectralEarth, integrating a spectral adapter into classical vision backbones to accommodate the unique characteristics of HSI. …”
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Harnessing quantum power: Revolutionizing materials design through advanced quantum computation by Zikang Guo, Rui Li, Xianfeng He, Jiang Guo, Shenghong Ju

“…We introduce the loop framework for QUBO‐empowered materials design, including constructing high‐quality datasets that capture critical material properties, employing tailored computational methods for precise material modeling, developing advanced figures of merit to evaluate performance metrics, and utilizing quantum optimization algorithms to discover optimal materials. …”
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Position-Aware Graph Neural Network for Few-Shot SAR Target Classification by Jia Zheng, Ming Li, Peng Zhang, Yan Wu, Hongmeng Chen

“…Experiments on OpenSARShip and MSTAR datasets demonstrate that the proposed PA-GNN can achieve comparable classification results compared with other FSL algorithms.…”
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KEDM: Knowledge-Embedded Diffusion Model for Infrared Image Destriping by Lingxiao Li, Xin Wang, Dan Huang, Yunan He, Zhuqiang Zhong, Qingling Xia

“…Empirical evaluations on several benchmark datasets demonstrate that the proposed KEDM outperforms other state-of-the-art destriping algorithms in terms of visual quality and quantitative metrics, validating its excellent performance.…”
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Lossless Compression with Trie-Based Shared Dictionary for Omics Data in Edge–Cloud Frameworks by Rani Adam, Daniel R. Catchpoole, Simeon J. Simoff, Zhonglin Qu, Paul J. Kennedy, Quang Vinh Nguyen

“…This paper introduces a lossless compression method that integrates Trie-based shared dictionaries within an edge–cloud architecture. …”
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