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  1. 12861

    D2D cooperative caching strategy based on graph collaborative filtering model by Ningjiang CHEN, Linming LIAN, Pingjie OU, Xuemei YUAN

    Published 2023-07-01
    “…A D2D cooperative caching strategy based on graph collaborative filtering model was proposed for the problem of difficulty in obtaining sufficient data to predict user preferences in device-to-device (D2D) caching due to the limited signal coverage of base stations.Firstly, a graph collaborative filtering model was constructed, which captured the higher-order connectivity information in the user-content interaction graph through a multilayer graph convolutional neural network, and a multilayer perceptron was used to learn the nonlinear relationship between users and content to predict user preferences.Secondly, in order to minimize the average access delay, considering user preference and cache delay benefit, the cache content placement problem was modeled as a Markov decision process model, and a cooperative cache algorithm based on deep reinforcement learning was designed to solve it.Simulation experiments show that the proposed caching strategy achieves optimal performance compared with existing caching strategies for different content types, user densities, and D2D communication distance parameters.…”
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  2. 12862

    Artificial intelligence in drug development: reshaping the therapeutic landscape by Sarfaraz K. Niazi, Zamara Mariam

    Published 2025-02-01
    “…Over the past 30 years, machine learning, deep learning, and neural networks have revolutionized drug design, target identification, and clinical trial predictions. AI has boosted pharmaceutical R&D (research and development) by identifying new therapeutic targets, improving chemical designs, and predicting complicated protein structures. …”
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  3. 12863

    A mode of action protein based approach that characterizes the relationships among most major diseases by Hongyi Zhou, Brice Edelman, Jeffrey Skolnick

    Published 2025-03-01
    “…Abstract Disease classification is important for understanding disease commonalities on both the phenotypical and molecular levels. Based on predicted disease mode of action (MOA) proteins, our algorithm PICMOA (Pan-disease Classification in Mode of Action Protein Space) classifies 3526 diseases across 20 clinically classified classifications (ICD10-CM major classifications). …”
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  4. 12864

    Classification of periodontitis stage and grade using natural language processing techniques. by Nazila Ameli, Tahereh Firoozi, Monica Gibson, Hollis Lai

    Published 2024-12-01
    “…Our proposed BERT model predicted the patients' stage and grade with 77% and 75% accuracy, respectively. …”
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  5. 12865

    Implicit Is Not Enough: Explicitly Enforcing Anatomical Priors inside Landmark Localization Models by Simon Johannes Joham, Arnela Hadzic, Martin Urschler

    Published 2024-09-01
    “…Currently, Anatomical Landmark Localization (ALL) is mainly solved by deep-learning methods, which cannot guarantee robust ALL predictions; there may always be outlier predictions that are far from their ground truth locations due to out-of-distribution inputs. …”
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  6. 12866

    Hull form optimization of fully parameterized small ships using characteristic curves and deep neural networks by Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo

    Published 2024-01-01
    “…To address this issue, this paper proposes an approach that involves defining a range of hull forms with characteristic curves, predicting their performance using Deep Neural Networks (DNNs), and subsequently determining the optimal hull form based on these predictions. …”
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  7. 12867

    SPINE: SParse eIgengene NEtwork linking gene expression clusters in Dehalococcoides mccartyi to perturbations in experimental conditions. by Cresten B Mansfeldt, Benjamin A Logsdon, Garrett E Debs, Ruth E Richardson

    Published 2015-01-01
    “…Based on the model predictions, we discovered new response mechanisms for DMC, notably when the bacterium is exposed to solvent toxicity. …”
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  8. 12868

    Performance of quantum approximate optimization with quantum error detection by Zichang He, David Amaro, Ruslan Shaydulin, Marco Pistoia

    Published 2025-05-01
    “…Abstract The quantum approximate optimization algorithm (QAOA) is a promising candidate for scaling up to tackle real-world applications. …”
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  9. 12869

    THE MODEL OF FORECASTING THE EXCHANGE RATE OF THE RUBLE IN OPERATIONAL PLANNING AND MANAGEMENT FINANCIAL AND ECONOMIC ACTIVITY by Alexander Gladilin, Olga Gridina

    Published 2022-05-01
    “…In the article the questions of creation of adequate models that predict the dependence of the exchange rate of the national currency on the price of oil for use in operational planning and forecasting offinancial and economic activity of enterprises and organizations. …”
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  10. 12870

    Clinical and neurophysiological predictors of the functional outcome in right-hemisphere stroke by Francesco Di Gregorio, Giada Lullini, Silvia Orlandi, Valeria Petrone, Enrico Ferrucci, Emanuela Casanova, Vincenzo Romei, Fabio La Porta

    Published 2025-03-01
    “…Then, the between-group discriminative EEG measures and the motor/cognitive scales were used to feed a machine learning algorithm to predict FIM scores at discharge and the length of hospitalization (LoH). …”
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  11. 12871

    Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models by Xiuxian Chen, Guzhong Chen, Kunchi Xie, Jie Cheng, Jiahui Chen, Zhen Song, Zhiwen Qi

    Published 2025-09-01
    “…Lastly, the PSO algorithm is employed to search the latent space for optimal IL structures with the highest predicted solubility. …”
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  12. 12872

    Closing the Open System by Nina Stener Jørgensen, Guillaume Laplante-Anfossi

    Published 2023-03-01
    “…The review of the programme questions how the probability distributions Schöffer included in the algorithm to ensure a random treatment of predictable city data was imagined to avoid stagnation, repetition and programmatic saturation, all elements essential to maintaining the tower’s open framework. …”
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  13. 12873

    Gestational diabetes mellitus and obesity: effects on offspring by O. V. Rozhkova, O. V. Remneva, N. I. Fadeeva, Yu. V. Korenovskiy, S. D. Yavorskaya

    Published 2021-07-01
    “…CHAID method (Chi Squared Automatic Interaction Detection) was used to create an algorithm for predicting adverse perinatal outcomes in GDМ. …”
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  14. 12874

    Construction of Integrated Platform for Eco-Sustainable Tourism and Marketing in Southeast Asia Based on Machine Learning by Yi-Tui Chen, Yi-Min Li, Tzu-Wen Tseng

    Published 2022-01-01
    “…Therefore, this study proposed a platform-related algorithm based on machine learning to build the integration of eco-sustainable tourism and marketing in Southeast Asia and used a collaborative filtering algorithm and a route generation algorithm to recommend information or predict specific needs for specific tourists. …”
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  15. 12875

    An Expert Fitness Diagnosis System Based on Elastic Cloud Computing by Kevin C. Tseng, Chia-Chuan Wu

    Published 2014-01-01
    “…It predicts the required resources in the future according to the exponential moving average of past observations. …”
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  16. 12876

    Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy by Wei Wu, Qihan Fu, Lulu Liu, Yi Zheng, Hangyu Zhang, Peng Zhao, Weijia Fang, Xuanwen Bao, Shaobing Cheng, Xiaomeng Dai, Xudong Zhu, Zhou Tong, Fanglong Liu

    Published 2020-10-01
    “…A more homogeneous highly expressed pattern of PD1 was observed in CD8+ T cells from MSI colon cancer; however, a small subgroup of CD8+ T cells with high expression of checkpoint molecules was identified in MSS patients. A random forest algorithm predicted important mutations that were associated with MSI status in the TCGA colon cancer cohort, and our in-house cohort validated higher frequencies of BRAF, ARID1A, RNF43, and KM2B mutations in MSI colon cancer. …”
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  17. 12877

    Research and practice on self-organization architecture of smart pipe in mobile internet by Fei XUE, Yuhui XU, Liang ZHANG, Ying LI

    Published 2018-09-01
    “…According to the 3GPP specification,a new self-organization network of smart pipe in mobile internet was addressed.By introducing integrated policy control function,the external signals were supervised periodically,and the best optimized network strategies were predicted by the recurrent neural network algorithm,delivered by PCRF,and updated automatically with feedback of the regulations.This solution was effectively applied in scenarios such as speed limit of large traffic users,network protection under high load,and online advertisement recommendation etc.…”
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  18. 12878

    Strong verb lemmas from a corpus of old english. Advances and issues by Darío Metola Rodríguez

    Published 2017-07-01
    “…The conclusions of the article insist on the limits of automatic lemmatisation as well as the paths of refinement of the lemmatisation method in order to accomodate less predictable forms.…”
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  19. 12879

    Forecasting Lakes' Chlorophyll Concentrations Using Satellite Images and Generative Adversarial Networks by Nikolaos Nagkoulis, Giorgos Vasiloudis, Anastasia Moumtzidou, Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Kompatsiaris

    Published 2024-10-01
    “…Using past measurements to predict future conditions remains a challenging task, because of the complexity of the natural phenomena that are involved, with great potential in terms of water resources management. …”
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  20. 12880

    Sequential Inversion for Helicopter Time-Domain Electromagnetics Based on a Regularized Extended Kalman Filtering by Sirui Zhou, Jun Lin, Chuandong Jiang, Haigen Zhou, Yanzhang Wang

    Published 2025-01-01
    “…In this article, we propose a sequential inversion method for HTEM based on the regularized extended Kalman filter (REKF). The REKF algorithm is used to predict the current inversion result at a given time by using the inversion result from the previous moment, and predictions are corrected with the observed data at that specific time. …”
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