Bayesian-Optimized Multi-Task Gaussian Process Regression With Composite Kernels for Soybean Oil Futures Forecasting by Hui-Dong Yin, Yi-Yang Li

“…Results confirm the model’s capacity to disentangle complex market patterns while maintaining computational tractability. …”
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Predicting dementia from primary care records: A systematic review and meta-analysis. by Elizabeth Ford, Nicholas Greenslade, Priya Paudyal, Stephen Bremner, Helen E Smith, Sube Banerjee, Shanu Sadhwani, Philip Rooney, Seb Oliver, Jackie Cassell

“…Variables in the primary care record may indicate risk of developing dementia, and could be combined in a predictive model to help find patients who are missing a diagnosis. …”
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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…In this work, we present QProteoML as an integration of quantum techniques purposefully developed to deal with high-dimensional, imbalanced and redundant data. …”
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Scientific geovisualization of the dynamics of Sargassum dispersion and landfall in the Caribbean, based on satellite imagery and numerical forecasts. by Francisco Javier Osorno-Covarrubias, Jorge Prado Molina, Gabriela Gómez-Rodríguez, Uriel Mendoza, Stéphane Couturier

“…In this study, we present the interactive geovisualization and discuss its potential for improving the scientific understanding of Sargassum dispersal and landfall patterns, as well as its potential for the implementation of coastal management policies. …”
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RNA modification gene WDR4 facilitates tumor progression and immunotherapy resistance in breast cancer by Yongzhou Luo, Wenwen Tian, Da Kang, Linyu Wu, Hailin Tang, Sifen Wang, Chao Zhang, Yi Xie, Yue Zhang, Jindong Xie, Xinpei Deng, Hao Zou, Hao Wu, Huan Lin, Weidong Wei

“…Methods: Genes related to thirteen RNA modification patterns were integrated for establishing a nine-gene-containing signature-RMscore. …”
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LcProt: Proteomics‐based identification of plasma biomarkers for lung cancer multievent, a multicentre study by Hengrui Liang, Runchen Wang, Ran Cheng, Zhiming Ye, Na Zhao, Xiaohong Zhao, Ying Huang, Zhanpeng Jiang, Wangzhong Li, Jianqi Zheng, Hongsheng Deng, Yu Jiang, Yuechun Lin, Yun Yan, Lei Song, Jie Li, Xin Xu, Wenhua Liang, Jun Liu, Jianxing He

“…Key points Our study developed an innovative nanomaterial, Zeolite NaY, which addressed the masking effect and improved the depth of the proteome. …”
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Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

“…However, the classification of shrublands proved challenging due to their mixed composition and unique spatial patterns, resulting in lower accuracies. Feature importance analysis demonstrated the value of the enhanced map composition, and applying the LandTrendr algorithm simplified the diachronic land use and land cover (LULC) classification and change analysis by supporting automatic training data collection. …”
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Exploration of the ubiquitination-related molecular classification and signature to predict the survival and immune microenvironment in colon cancer by Ji-Zhong Xu, Tian-Qi Wan, Jin-Song Su, Jun-Min Song

“…Subtype feature genes were selected through Lasso logistic regression and SVM-RFE algorithm. …”
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Well Performance from Numerical Methods to Machine Learning Approach: Applications in Multiple Fractured Shale Reservoirs by Kailei Liu, Boyue Xu, Changjea Kim, Jing Fu

“…Then, feature selection is performed to determine the key factors. …”
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Deciphering hypoxia’s role in hepatocellular carcinoma prognosis with single-cell approaches by Jun Liang, Di Chen, Huiyu Liang

“…To probe the effects of hypoxia on HCC invasion, we developed the Cell Hypoxia-Related Prognostic Feature (CHPF). …”
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Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks by Magdalena Fafrowicz, Marcin Tutajewski, Igor Sieradzki, Jeremi K. Ochab, Jeremi K. Ochab, Anna Ceglarek-Sroka, Koryna Lewandowska, Tadeusz Marek, Barbara Sikora-Wachowicz, Igor T. Podolak, Paweł Oświęcimka, Paweł Oświęcimka, Paweł Oświęcimka

“…The best performance was achieved by the LGBM classifier with 1-time point input data during memory retrieval and a convolutional neural network during the encoding phase. Additionally, we developed an algorithm that took into account feature correlations to estimate the most important brain regions for the model's accuracy. …”
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Temporal Coupling of Brain Signals and Fine Motor Output Using Affordable EEG by Adam Gyula Nemes, Adam Gyulai, Adam Szarvas, Erno Nemeth, Kristof Tajti, Viktor Toth, Gyorgy Eigner

“…This multimodal approach enhances dataset quality by enabling millisecond-precise alignment between stimulus presentation, cortical activation patterns, and resultant motor behavior—a critical feature lacking in most publicly available motor-related EEG datasets. …”
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Deep learning model for diagnosis of thyroid nodules with size less than 1 cm: A multicenter, retrospective study by Na Feng, Shanshan Zhao, Kai Wang, Peizhe Chen, Yunpeng Wang, Yuan Gao, Zhengping Wang, Yidan Lu, Chen Chen, Jincao Yao, Zhikai Lei, Dong Xu

“…Results: TNT-Net achieved an area under the curve (AUC) of 0.953 (95 % confidence interval (CI): 0.934, 0.969) on the internal test set and 0.941 (95 % CI: 0.921, 0.957) on the external test set, significantly outperforming traditional deep convolutional neural network models and single-channel swin transformer model, whose AUCs ranged from 0.800 (95 % CI: 0.759, 0.837) to 0.856 (95 % CI: 0.819, 0.881). Furthermore, feature heatmap visualization showed that TNT-Net could extract richer and more energetic malignant nodule patterns. …”
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Exploring the potential and limitations of deep learning and explainable AI for longitudinal life course analysis by Helen Coupland, Neil Scheidwasser, Alexandros Katsiferis, Megan Davies, Seth Flaxman, Naja Hulvej Rod, Swapnil Mishra, Samir Bhatt, H. Juliette T. Unwin

“…However, significant gaps remain in understanding their utility and limitations, especially for sparse longitudinal life course data and how the influential patterns identified using explainability are linked to underlying causal mechanisms. …”
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Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

“…Since the outbreak of COVID-19, there has been an influx of research on predictive modelling, with artificial intelligence (AI) techniques, particularly machine learning (ML) methods, becoming the dominant research direction due to their superior capability in processing multidimensional datasets and capturing complex nonlinear transmission patterns. We systematically reviewed COVID-19 ML prediction models developed under the background of the epidemic using the PRISMA method. …”
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SYNESTHESIA IN THE NOVEL BY M. PAVIĆ: “LANDSCAPE PAINTED WITH TEA” by Nataliya L. Bilyk

“…The specific nature of certain components of the mechanism and the patterns of functioning inherent in synesthesia, and above all, meaning-making, should be accepted in a generalized aspect. …”
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Multi-scale machine learning model predicts muscle and functional disease progression by Silvia S. Blemker, Lara Riem, Olivia DuCharme, Megan Pinette, Kathryn Eve Costanzo, Emma Weatherley, Jeff Statland, Stephen J. Tapscott, Leo H. Wang, Dennis W. W. Shaw, Xing Song, Doris Leung, Seth D. Friedman

“…A three-stage random forest model was developed to predict annualized changes in muscle composition and a functional outcome (timed up-and-go (TUG)). …”
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Media Framing and Portrayals of Ransomware Impacts on Informatics, Employees, and Patients: Systematic Media Literature Review by Atiya Avery, Elizabeth White Baker, Brittany Wright, Ishmael Avery, Dream Gomez

“…First, an analysis of the geographic prevalence showed that the United States (34/48, 71%), followed to a lesser extent by India (4/48, 8%) and Canada (3/48, 6%), featured more prominently in our sample. Second, there were no apparent year-to-year patterns in the occurrence of reported events of ransomware attacks on health care provider information systems. …”
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Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection by Jia Xu, Han Pu, Dong Wang

“…To address this issue, we propose a shared feature map cache design for asynchronous convolution in the accelerators presented in this paper. …”
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A novel measurement system for unattended, in situ characterization of carbonaceous aerosols by A. Keller, P. Specht, P. Steigmeier, E. Weingartner

“…To address this issue we have developed the fast thermal carbon totalizator (FATCAT). …”
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