External Validation of the International Prognosis Prediction Model of IgA Nephropathy by Lichao Hu, Yi Fang, Jiaxin Huang, Jin Liu, Lingling Xu, Weichun He

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Construction of an immune prediction model for osteosarcoma based on coagulation-related genes by Ye Jiang, Huiqi Yuan, Yongping Cao

“…Furthermore, a prognostic risk model constructed using coagulation system-related genes (CRGs) demonstrated solid predictive ability for patient survival. …”
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Revolutionizing heart attack prognosis: Introducing an innovative regression model for prediction by Hanaa Albanna, Madhav Raj Theeng Tamang, Chandan Patel, Mhd Saeed Sharif

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A multivariate time series prediction model based on the KAN network by Yunji Long, Xue Qin

“…Abstract Time series forecasting is crucial in various fields such as financial markets and weather prediction. Although mainstream deep learning models like RNNs and CNNs have made some progress in capturing short-term patterns, they still fall short in handling long-range dependencies and complex interactions. …”
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Predicting the Time of Bus Arrival for Public Transportation by Time Series Models by Süleyman Mete, Erkan Çelik, Muhammet Gül

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An Ensemble Model for Predicting Cardiovascular Disease utilizing Nature Inspired Optimization by Annwesha Banerjee Majumder, Somsubhra Gupta, Sourav Majumder, Dharmpal Singh

“… This paper represents an efficient model for heart disease prediction model utilizing an ensemble mechanism optimized through BAT algorithm. …”
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Stock Price Prediction in the Financial Market Using Machine Learning Models by Diogo M. Teixeira, Ramiro S. Barbosa

“…The complexity of advanced models such as XGBoost and GRU is reflected in their overall performance, suggesting that they can be particularly effective at capturing patterns and making accurate predictions in more complex time series, such as stock prices.…”
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Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling by Patricia Virginia de Santana Lima, David Venâncio da Cruz, Albaro Ramon Paiva Sanz

“… The development of models to predict the behavior of the Bitcoin cryptocurrency, using a public database (Yahoo! …”
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Dynamic ensemble-based machine learning models for predicting pest populations by Ankit Kumar Singh, Md Yeasin, Ranjit Kumar Paul, A. K. Paul, Anita Sarkar

“…Furthermore, ensemble algorithms help in the utilization of several models rather than being dependent on a single model. …”
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Predicting Health Spending in Turkey Using the GPR, SVR, and DT Models by Didem Güleryüz

“…Therefore, the SVR model has accurate prediction results with the highest R2 and the least root mean square error values in the testing phase. …”
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New Perturbation Model for Prediction of Amino Acid and Peptide Activity Coefficients

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Prognostic model for predicting recurrence in breast cancer patients in Saudi Arabia by Ousman Khan, Jimoh Olawale Ajadi, Fahad Almsned, Hani Almohanna, Amjad Alrasheed, Ridwan A. Sanusi, Nurudeen A. Adegoke

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Simulation and prediction of rural population changes using agent-based modeling. by Shanshan Huang, Yao Huang, Shitai Bao, Jianfang Wang, Siying Chen

“…Using two representative villages as study areas, the results were validated by comparing them with actual population data and predictions made by the Leslie model. The findings demonstrate the following: 1) the agent-based modeling effectively captures the dynamics of births, deaths, and migrations at the micro level, elucidating the underlying determinants of rural population retention. 2) In economically disadvantaged villages, the total population, labor force, and proportion of adolescents have significantly declined. …”
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The Prognosis Prediction Model for Endometrial Cancer Based on DNA Methylation Signature by Ran Ran, Ming Wang, Jinwei Miao

“…By LASSO‐Cox regression analyses, a recurrence prediction model and a prognostic‐related model were constructed based on methylation‐related genes in the TCGA training cohort. …”
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Attack scenarios reasoning,hypothesizing and predicting based on capability transition model by TIAN Zhi-hong1, ZHANG Wei-zhe1, ZHANG Yong-zheng2, ZHANG Hong-li 1, LI Yang2, JIANG Wei1

“…To construct attack scenarios and predict intrusion intents automatically,a real-time alert correlation approach based on capability transition model was proposed.By highly abstracting the reasoning evidences,the process complexity is effectively reduced.Experiment results on the DARPA2000 IDS test dataset indicate that the method is effective and efficient.…”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“… This paper proposes an approach for constructing a system for career prediction by applying the eXtreme Gradient Boosting (XGBoost) Decision Tree model to the academic results of Ho Chi Minh International University’s School of Computer Science and Engineering graduates in the past 5 years. …”
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The clinical prediction model to distinguish between colonization and infection by Klebsiella pneumoniae by Xiaoyu Zhang, Xifan Zhang, Deng Zhang, Jing Xu, Jingping Zhang, Xin Zhang

“…Six predictive models were constructed using 15 key influencing factors, including Classification and Regression Trees (CART), C5.0, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), Random Forest (RF), and Nomogram. …”
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hybrid model to improve reference evapotranspiration prediction: Integrating ANN and PSO by Hadeel Essa, Salah L. Zubaidi

“…In order to estimate monthly ETo, this study tested the prediction abilities of a unique hybrid methodology that coupled data pre-processing with a hybrid model composed of an artificial neural network (ANN) and particle swarm optimisation (PSO). …”
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Predicting Social Unrest Events with Hidden Markov Models Using GDELT by Fengcai Qiao, Pei Li, Xin Zhang, Zhaoyun Ding, Jiajun Cheng, Hui Wang

“…In this paper, we use autocoded events dataset GDELT (Global Data on Events, Location, and Tone) to build a Hidden Markov Models (HMMs) based framework to predict indicators associated with country instability. …”
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Research on 5G core network service model intelligent prediction by Nan FENG, Helin LIU, Quan ZHOU, Haijun YANG, Mineng FU, Daping ZHONG

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