Enhancing Power Allocation in DAS: A Hybrid Machine Learning and Reinforcement Learning Model by S. Gnanasekar, K. C. Sriharipriya

“…The proposed method combines Machine Learning (ML) for predictive modeling with Multi-Agent Reinforcement Learning (MARL) for real-time coordination among RAUs. …”
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Novel Insights from Comprehensive Bioinformatics Analysis Utilizing Large-Scale Human Transcriptomes and Experimental Validation: The Role of Autophagy in Periodontitis by Liu F, Zhu Z, Zou H, Huang Z, Xiao S, Li Z

“…Subsequently, a comprehensive analysis of immune cell infiltrate utilizing the CIBERSORT algorithm was performed. Finally, leveraging the DSigDB database, potential candidate drugs for periodontitis treatment targeting autophagy were predicted.Results: A total of 79 genes have been identified as DEARGs in periodontitis. …”
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Utility of positron emission tomography–computed tomography in the evaluation of fever of unknown origin in a resource-limited tropical nation by Sohini Das, Sowmya Sathyendra, Julie Hephzibah, Reka Karuppusami, Karthik Gunasekaran, Nylla Shanthly, Angel Miraclin, Ramya Iyadurai

“…We also looked at laboratory parameters as predictors of contributory PET-CT scans and propose an algorithm for evaluation of FUO in resource-limited tropical regions. …”
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Relationship Between Sepsis Phenotypes and Treatment Characteristics of Patients with Viral and Bacterial Pneumonia by I. A. Ruslyakova, E. Z. Shamsutdinova, L. B. Gaikovaya

“…New subgroups of patients with severe community-acquired pneumonia (SCAP) are hardly predicted by the use of clinical covariates; clusterization may significantly improve diagnostic approaches and facilitate the adaptation of specific treatment modalities to patient’s individual characteristics.The aim of the study. …”
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Single-cell and bulk transcriptome analyses reveal elevated amino acid metabolism promoting tumor-directed immune evasion in colorectal cancer by Tianyue Sun, Yan Chen, Ying-Xuan Chen

“…Additionally, LASSO and Cox regression analyses were conducted to construct an AA metabolism-related risk score for predicting prognosis and drug sensitivity across multiple bulk transcriptome cohorts.ResultsThis study identified a link between elevated amino acid metabolism in CRC epithelial cells and resistance to PD-1 blockade therapy. …”
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Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province by Yao Zhang, Qiao-Lin Wang, Wei Peng, Meng-Yuan Zhang, Yao Qin, Lun Zhang, Rong-Jie Wei, Dian-Ju Kang

“…The eXtreme Gradient Boosting (XGBoost) algorithm was employed to assess the influence of key environmental features, including precipitation, temperature, PM10, potential evaporation, vegetation cover, and NDVI, on BD incidence. …”
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ПРОГНОЗИРОВАНИЕ РИСКА НАЛИЧИЯ ВОСПАЛИТЕЛЬНЫХ ЗАБОЛЕВАНИЙ КИШЕЧНИКА У ПАЦИЕНТОВ БЕЗ ЛАБОРАТОРНЫХ ПРИЗНАКОВ ВОСПАЛЕНИЯ... by Yuliya Abbyasovna Khalitova, Yuliya Valerevna Myakisheva, Artem Viktorovich Lyamin, Alena Anatolevna Ereshchenko, Anna Vitalevna Yanchenko

“…An algorithm for predicting the risk of IBD in patients without non-specific laboratory criteria of inflammation was proposed. …”
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An explainable GeoAI approach for the multimodal analysis of urban human dynamics: a case study for the COVID-19 pandemic in Rio de Janeiro by David Hanny, Dorian Arifi, Steffen Knoblauch, Bernd Resch, Sven Lautenbach, Alexander Zipf, Antonio Augusto de Aragão Rocha

“…We then compare the predictive power of the selected features against those identified by traditional feature selection methods. …”
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Simulation and Modelling of C+L+S Multiband Optical Transmission for the OCATA Time Domain Digital Twin by Prasunika Khare, Nelson Costa, Marc Ruiz, Antonio Napoli, Jaume Comellas, Joao Pedro, Luis Velasco

“…Being able to predict the optical signal in the time domain, as it will be received after propagation, opens opportunities for automating network operation, including connection provisioning and failure management. …”
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China by Shaowu Lin, Sicheng Li, Ya Fang

“…The developed machine learning models with high predictive accuracy, suggest the potential of Kinect-based gait assessment as a real-time and cost-effective screening tool for older adults with depressive symptoms.…”
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Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients by Jacob C. Jentzer, Eunjung Lee, Zachi Attia, Dustin Hillerson, Garvan C. Kane, Francisco Lopez‐Jimenez, Peter A. Noseworthy, Paul A. Friedman, Jae K. Oh

“…An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been examined in cardiac intensive care units. …”
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Market and cadastral data comparison for the real estate market value forecasting by M. B. Laskin, P. A. Cherkesova

“…The theoretical significance of the work is the proposed algorithm for estimating the most probable trajectory of the market value of the investigated object, based on the conditional multivariate log-normal distribution for a given value of the cadastral value. …”
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Stepwise autonomous orbit determination of large LEO constellations by GNSS observations with partial inter-satellite ranging by Yuanxi Yang, Xiaoyong Song

“…The difference of the adaptive stepwise OD algorithm is that the covariance matrix of the predicted orbit parameters based on the dynamic model is modified by an adaptive factor. …”
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Artificial intelligence based surgical support for experimental laparoscopic Nissen fundoplication by Holger Till, Ciro Esposito, Chung Kwong Yeung, Dariusz Patkowski, Sameh Shehata, Steve Rothenberg, Georg Singer, Tristan Till

“…For 3/5 classifiers the results remained identical; detection of incomplete and too loose LNFs showed a slight decline in predictive power.ConclusionThis experimental study demonstrates that an AI/CV algorithm can effectively detect VQIs in digital images of Nissen fundoplications. …”
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Research on Non-Random Vibration Analysis of Concrete Pump Truck Boom Based on Dynamic Excitation by Weixin Zhou, Wubin Xu, Bing Li, Yuanbin Xiao, Xianyu Liu, Hanwen Zhang, Bo Xu

“…The technique can reliably predict the dynamic displacement boundary and control the casting position deviation within a predefined range by accurately predicting the dynamic displacement range of the pump truck’s boom end and efficiently constructing the displacement envelope under uncertain dynamic excitation. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Thus, scientifically assessing and predicting geological disasters and formulating disaster prevention and mitigation policies are of critical importance for promoting regional sustainable development. …”
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Multi-objective optimization of sustainable cement-zeolite improved sand based on life cycle assessment and artificial intelligence [version 1; peer review: 1 approved, 2 approved... by Hossein MolaAbasi, Satinder Kaur Brar, Amin Tanhadoust, Sepideh Nasrollahpour, Omolbanin Ataee, Moncef L. Nehdi

“…This study proposes a multi-objective optimization approach using back-propagation neural network (BPNN) to predict the mechanical strength, along with an adaptive geometry estimation-based multi-objective evolutionary algorithm (AGE-MOEA) to identify the best parameters for cement-zeolite-improved sand, filling a long-lasting research gap. …”
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A novel mitochondrial quality regulation gene signature for anticipating prognosis, TME, and therapeutic response in LUAD by multi-omics analysis and experimental verification by Lijun Zeng, Sixuan Wu, Zhimin Li, Yuanbin Tang, Yeru Tan, Renji Liang, Yuehua Li

“…Utilizing the LASSO algorithm and multivariate COX regression, a predictive risk model was created. …”
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Increasing Systemic Resilience to Socioeconomic Challenges: Modeling the Dynamics of Liquidity Flows and Systemic Risks Using Navier–Stokes Equations by Davit Gondauri, Nino Chedia, Vakhtang Tsintsadze

“…The methodology is based on a mixed approach: econometric testing, Fourier analysis, stochastic simulations, and AI-algorithm tuning, which together provide dynamic testing, calibration, and forecasting capabilities of the model. …”
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Risk analysis of the association between EASIX and all-cause mortality in critical ill patients with atrial fibrillation: a retrospective study from MIMIC-IV database by Yu Xia, Anfeng Liang, Mei Wang, Jianlin Zhang

“…The AUC showed that the performance of EASIX in predicting both short-term and long-term all-cause mortality was comparable to the SOFA and higher than the CHA₂DS₂–VASc score. …”
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