TRACE Model: Predicting Treatment Response to Transarterial Chemoembolization in Unresectable Hepatocellular Carcinoma by Wang W, Zhang Q, Cui Y, Zhang S, Li B, Xia T, Song Y, Zhou S, Ye F, Xiao W, Cao K, Chi Y, Qu J, Zhou G, Chen Z, Zhang T, Chen X, Ju S, Wang YC

“…In contrast, none of the published scoring systems, including ART, SNACOR or ABCR score, demonstrated significant differences between the risk groups in OS prediction.Conclusion: The TRACE model exhibited favorable predictive capability for six-month TACE response, and holds potential as a marker for long-term survival outcomes.Keywords: hepatocellular carcinoma, treatment response, transarterial chemoembolization, radiomics…”
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Multi-target property prediction and optimization using latent spaces of generative model by Anirudh Jain, Markus Heinonen, Heikki Käsnänen, Julius Sipilä, Samuel Kaski

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AGCN-T: A Traffic Flow Prediction Model for Spatial-Temporal Network Dynamics by Jian Feng, Lang Yu, Rui Ma

“…Aiming at the lack of the ability to model complex and dynamic spatial-temporal dependencies in current research, this paper proposes a traffic flow prediction model Attention based Graph Convolution Network (GCN) and Transformer (AGCN-T) to model spatial-temporal network dynamics of traffic flow, which can extract dynamic spatial dependence and long-distance temporal dependence to improve the accuracy of multistep traffic prediction. …”
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Research on the Large Deformation Prediction Model and Supporting Measures of Soft Rock Tunnel by Junying Rao, Yonghu Tao, Peng Xiong, Chongxin Nie, Hao Peng, Yanghao Xue, Zuowei Xi

“…Results show that the gray model has high prediction accuracy, the best prediction time is one week, and the maximum error is only 2.99%; with the decrease in d, resin bolt support has a significant supporting effect compared with mortar bolt support, with Smax.M and σmax·M reduced by 64.38% and 10.35%, respectively; as the L of bolt increases, compared with the mortar bolt support, the resin bolt support has a more obvious restraining effect on the surrounding rock deformation, and Smax·M and σmax·M are reduced by 28.20% and 10.00%, respectively; when 4.5 m < L < 6.0 m and 0.6 m < d < 0.7 m, resin bolt support should be adopted; in other ranges, mortar bolt support or resin bolt support has a less significant difference in controlling surrounding rock deformation.…”
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CFP-AL: Combining Model Features and Prediction for Active Learning in Sentence Classification by Keuntae Kim, Yong Suk Choi

“…In this study, we propose a new insight, CFP-AL (Combining model Features and Prediction for Active Learning), from the perspective of feature space by analyzing and diagnosing methods that have shown good performance in NLP (Natural Language Processing) sentence classification. …”
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Failure prediction of T-peel adhesive joints by different cohesive laws and modelling approaches by Alessandro Pirondi

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Prediction on the Seasonal Behavior of Hydrogen Sulfide Using a Neural Network Model by Byungwhan Kim, Joogong Lee, Jungyoung Jang, Dongil Han, Ki-Hyun Kim

“…Models to predict seasonal hydrogen sulfide (H2S) concentrations were constructed using neural networks. …”
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An Innovative Dynamic Model for Predicting Typhoon Track Deflections over Complex Terrain by Hung-Cheng Chen

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Intelligent Feature Selection Ensemble Model for Price Prediction in Real Estate Markets by Daniel Cristóbal Andrade-Girón, William Joel Marin-Rodriguez, Marcelo Gumercindo Zuñiga-Rojas

Subjects: “…ensemble model…”
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Prenatal depression level prediction using ensemble based deep learning model by Abinaya Gopalakrishnan, Xujuan Zhou, Revathi Venkataraman, Raj Gururajan, Ka Ching Chan, Guohun Zhu, Niall Higgins

“…This culminated in the development of a novel EBDL model to accurately predict stress levels. Results:: We subsequently applied the ensemble based deep learning model on a testing dataset and our method proved to be 93.87 percent accurate, proving its superiority over the standard supervised classification models. …”
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Explaining the Earnings Management Prediction Model Using the Hybrid of Machine Learning Methods by Hassan Hassani, Esfandiar Malekian Kallehbasti, Yahya Kamyabi

“…This result was confirmed in all prediction methods. However, the results did not show the superiority of the relief-based feature selection model over the principal component analysis-based feature selection model in predicting real earnings management. …”
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Outcome prediction model for patients with unresectable hepatocellular carcinoma treated with targeted therapy by Qiang Ruan, Xiaohui Wang, Qiang Li, Yu Tao, Yang Xun, Hua Yang, Han Zhao, Jinfeng Lu, Dazhi Yang, Yifan Chen, Li Wei

“…Abstract There is no well-established model to predict the outcomes of patients with unresectable hepatocellular carcinoma (u-HCC) receiving targeted therapy. …”
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Modeling and Simulation: A Study on Predicting the Outbreak of COVID-19 in Saudi Arabia by Ahmed Msmali, Mutum Zico, Idir Mechai, Abdullah Ahmadini

“…The novel coronavirus disease (COVID-19) has resulted in an ongoing pandemic affecting the health system and economy of more than 200 countries worldwide. Mathematical models are used to predict the biological and epidemiological tendencies of an epidemic and to develop methods for controlling it. …”
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Pedestrian trajectory prediction model based on self-supervised spatiotemporal graph network by Shiji Yang, Xuezhong Xiao

“…To improve the accuracy of pedestrian trajectory prediction, the graph - based pedestrian trajectory modeling method in the pedestrian trajectory prediction scenario is effective. …”
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Regression-Based Modeling for Energy Demand Prediction in a Prototype Retail Manipulator by Piotr Kroczek, Krzysztof Lis, Piotr Przystałka

“…The present study proposes two regression-based models for predicting the energy consumption of a four-axis prototype retail manipulator. …”
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Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study by Eric Pulick, John Curtin, Yonatan Mintz

“…Digital sensing and predictive modeling can augment scarce clinician resources to expand and personalize patient care. …”
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Strong Prediction: Language Model Surprisal Explains Multiple N400 Effects by James A. Michaelov, Megan D. Bardolph, Cyma K. Van Petten, Benjamin K. Bergen, Seana Coulson

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Advanced neural network-based model for predicting court decisions on child custody by Mohammad Abrar, Abdu Salam, Faizan Ullah, Muhammad Nadeem, Hussain AlSalman, Muaadh Mukred, Farhan Amin

“…Thus to solve this issue, we propose a new neural network-based model for predicting court decisions on child custody. …”
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Model Constrained by Visual Hierarchy Improves Prediction of Neural Responses to Natural Scenes. by Ján Antolík, Sonja B Hofer, James A Bednar, Thomas D Mrsic-Flogel

“…When fit to recordings of a local population of mouse layer 2/3 V1 neurons, our model offers an accurate description of their response to natural images and significant improvement of prediction power over the current state-of-the-art methods. …”
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A Microscopic Prediction Model for Traffic Noise in Adjacent Regions to Arterial Roads by Ming LI, Jizhou LIU

“…To determine this impact magnitude, this paper proposes and validates a microscopic level method that locally predicts the total noise level and the spectral characteristics of traffic flow in the near-road region. …”
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