A Sparse Bayesian Technique to Learn the Frequency-Domain Active Regressors in OFDM Wireless Systems by Carlos Crespo-Cadenas, María José Madero-Ayora, Juan A. Becerra, Elías Marqués-Valderrama, Sergio Cruces

“…The FD-SBL algorithm is proposed to first identify the active FD regressors and estimate the coefficients of the PA model using a given symbol, and then, the coefficients are employed to predict the distortion of successive OFDM symbols. …”
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The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa by F. Merk, T. Schaffhauser, F. Anwar, Y. Tuo, J.-M. Cohard, M. Disse

“…Moreover, the benchmarking highlights that, if it only accounts for the LAI but disregards AET data, an optimization process's prediction of AET still yields an adequate performance with SWAT-T for all PET methods and land cover types. …”
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A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease by Giles Dixon, Hannah Thould, Matthew Wells, Krasimira Tsaneva-Atanasova, Chris J. Scotton, Michael A. Gibbons, Shaney L. Barratt, Jonathan C.L. Rodrigues

“…A modified CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) checklist was used for data extraction. …”
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THE RELATIONSHIP BETWEEN THE INDIVIDUAL GENETICALLY DETERMINED FACIAL PROFILE OF PATIENTS WITH A DISTAL OCCLUSION (ENGLE CLASS II) AND THE TYPE OF GROWTH OF THEIR FACIAL SKULL AND... by S.I. Doroshenko, O.Y. Opekha, V.V. Volkova

“…Jarabak methods has enabled a more detailed diagnosis of distal occlusion (Class II malocclusion) and the development of a comprehensive treatment algorithm with improved outcome prediction. …”
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Identification of Exosome-Associated Biomarkers in Diabetic Foot Ulcers: A Bioinformatics Analysis and Experimental Validation by Tianbo Li, Lei Gao, Jiangning Wang

“…Analyses included nomogram construction, functional and correlation analyses, immune infiltration, GSEA, gene co-expression and regulatory network construction, drug prediction, molecular docking, and RT-qPCR validation in clinical samples. …”
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Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic... by Peng Lyu, Na Xie, Xu-peng Shao, Shuai Xing, Xiao-yue Wang, Li-yun Duan, Xue Zhao, Jia-min Lu, Rong-fei Liu, Duo Zhang, Wei Lu, Kai-liang Fan

“…Abstract This study aims to predict and diagnose pediatric septic shock through the screening of immune infiltration-related biomarkers. …”
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Parallel Processing of Sobel Edge Detection on FPGA: Enhancing Real-Time Image Analysis by Sanmugasundaram Ravichandran, Hui-Kai Su, Wen-Kai Kuo, Dileepan Dhanasekaran, Manikandan Mahalingam, Jui-Pin Yang

“…This work focuses on algorithmic complex reduction by using eight directional approaches, and parallel processing leads to reducing the architectural utilization.…”
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Catalyzing early ovarian cancer detection: Platelet RNA-based precision screening by Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Hyejin Lee, Yeochan Kim, Sangick Park, Suyeon Lee, Dong Won Hwang, Heeyeon Kim, HyunA Jo, Untack Cho, Juwon Lee, Cheol Lee, TaeJin Ahn, Yong-Sang Song

“…If integrated with current screening methods, our algorithm holds promise for identifying ovarian or endometrial cancer in its early stages.…”
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Designing a Neural Observer to Estimate the State Variables of the Dynamical System of a Specific Class of Leukaemia by Yousef Farshidi, Reza Ghasemi, Aminin Sharafian Ardekani

“…In order to adjust the neural network weights, the error back propagation learning algorithm was implemented. First of all, in this algorithm, the system outputs are generated according to random weights. …”
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Deep learning based energy-efficient transmission control for STAR-RIS aided cell-free massive MIMO networks by Chihyun Song, Donghyun Lee, Yunseong Lee, Wonjong Noh, Sungrae Cho

“…From the simulations, it is revealed the proposed algorithm provides better energy performance than benchmarks, highlighting the benefits of STAR-RIS in the CF network.…”
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Immune Evasion Mechanism Mediated by ITPRIPL1 and Its Prognostic Implications in Glioma by Zou Xiaoyun, Ye Wenhao, Wu Huan, Yang Yuanyuan, Liu Changqing, Wen Hebao, Ma Caiyun

“…Ninety‐eight machine learning algorithm combinations were screened to identify the optimal predictive model. …”
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Synergizing Attribute-Guided Latent Space Exploration (AGLSE) with Classical Molecular Simulations to Design Potent Pep-Magnet Peptide Inhibitors to Abrogate SARS-CoV-2 Host Cell E... by Farhan Ullah, Aobo Xiao, Shahid Ullah, Na Yang, Min Lei, Liang Chen, Sheng Wang

“…Using artificial intelligence (AI), specifically variational autoencoders (VAE) and Wasserstein autoencoders (WAE), we were able to generate a latent space plot that can be surveyed for peptides with known properties and interpolated across a predictive vector between two defined points to identify novel peptides that exhibit dose-responsive antiviral activity. …”
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Association of estimated glucose disposal rate with atrial fibrillation, heart failure and cardiovascular mortality in patients with diabetes: a prospective cohort study from the U... by Zhen Tan, Yijun Liu, Lei Liu, Shuang Li, Xinrui Xue, Xiaoping Li, Hongqiang Ren

“…Polygenic Risk Score (PRS) analysis evaluated the joint effects of eGDR and PRS. Boruta algorithm filtered key predictive variables. Subgroup analysis was performed using cardiovascular high-risk factors, and mediation analysis explored the relationships of eGDR with the outcomes.ResultsSubjects with higher eGDR were more likely to be female, younger, more physically active, non-smoker, and non-drinker. …”
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PDT-regulated immune gene prognostic model reveals tumor microenvironment in colorectal cancer liver metastases by Jiachi Xu, Hui Zhou, Zhongtao Liu, Yunpeng Huang, Zijian Zhang, Heng Zou, Yongxiang Wang

“…Subsequently, utilizing single-cell sequencing data about liver metastasis, the colorectal cancer immune microenvironment reflected in the predictive model was analyzed, and a key gene set of the model was identified. …”
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Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool by Juan Francisco Morales, Marian Klose, Yannick Hoffert, Jagdeep T. Podichetty, Jackson Burton, Stephan Schmidt, Klaus Romero, Inish O'Doherty, Frank Martin, Martha Campbell‐Thompson, Michael J. Haller, Mark A. Atkinson, Sarah Kim

“…Using individual‐level data collected from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies, we previously developed a quantitative joint model to predict the time to T1D onset. We then applied trial‐specific inclusion/exclusion criteria, sample sizes in treatment and placebo arms, trial duration, assessment interval, and dropout rate. …”
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Hybrid Artificial-Intelligence-Based System for Unmanned Aerial Vehicle Detection, Localization, and Tracking Using Software-Defined Radio and Computer Vision Techniques by Pablo López-Muñoz, Luis Gimeno San Frutos, Christian Abarca, Francisco José Alegre, Jose Luis Calle, Jose F. Monserrat

“…Additionally, this module integrates a localization and tracking algorithm, allowing the tracking of the intruding UAV’s position. …”
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Multimodal identification of a rare head and neck cancer patient cohort in the clinical data warehouse of Greater Paris Teaching Hospital by A. La Rosa, M. Verdoux, P. Riebler, I. Lolli, C. Daniel, X. Tannier, S. Atallah, B. Baujat, E. Kempf

“…It showed a 91% sensitivity and a 95% specificity when relying on multiple data sources, with a 76% positive predictive value observed for rare histology identification compared with 43% for rare topography. …”
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Scalable Precision Psychiatry With an Objective Measure of Psychological Stress: Prospective Real-World Study by Helena Wang, Norman Farb, Bechara Saab

“…Algorithm predictions were compared against the efficacy of the individual’s self-selected sessions. …”
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Incremental mining of periodic patterns of inadequately informed communication data based on fuzzy segmentation of time series by Miaomiao Li

“…Subsequently, the partial weekly incremental pattern mining algorithm with a moving window scans the segmented data, extracting new periodic patterns using the maximum sub-pattern pandering tree algorithm. …”
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Machine learning-driven design of rare metal doped niobium alloys with enhanced strength and ductility by Zhenqiang Xiong, Zhaokun Song, Jianwei Li, Heran Wang, Xiaoxin Zhang, Bin Liang, Dong Wang

“…A comprehensive database of niobium alloys' properties was analyzed using feature engineering, and a high-accuracy prediction model, Gray Wolf Optimization-Extreme Learning Machine (GWO-ELM), was constructed, achieving R2 values of 0.95 and 0.88 for tensile strength and elongation, respectively. …”
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