Predictive Modeling of Lignocellulosic Content in Crop Straws Using NIR Spectroscopy by Yifan Zhao, Yingying Zhu, Yumeng Ren, Yu Lu, Chunling Yu, Geng Chen, Yu Hong, Qian Liu

“…Specifically, the cellulose PLS model achieved a prediction set coefficient of determination (R²_P) of 0.8983, root mean square error of prediction (RMSEP) of 0.6299, and residual predictive deviation (RPD) of 3.49. …”
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Construction of risk prediction model for dysphagia in hospitalized elderly patients with frailty by Yuzhu Lin, Chen Xu, Xue Song, Qin Tan, Xiaolei Lian

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Chronic lung lesions in COVID-19 survivors: predictive clinical model by Paulo A Lotufo, Juliana C Ferreira, Eloisa Bonfa, Anna S Levin, Rodrigo Caruso Chate, Marta Imamura, Esper G Kallas, Roger Chammas, Thais Mauad, Izabel Marcilio, Nelson Gouveia, Ricardo Nitrini, José Eduardo Krieger, Marcio Valente Yamada Sawamura, Michelle Louvaes Garcia, Cristiano Gomes, Guilherme Fonseca, Jorge Hallak, Luis Yu, Marcio Mancini, Maria Elizabeth Rossi, Thiago Avelino-Silva, Edivaldo M Utiyama, Aluisio C Segurado, Beatriz Perondi, Anna Miethke-Morais, Amanda C Montal, Leila Harima, Marjorie F Silva, Marcelo C Rocha, Maria Amélia de Jesus, Carolina Carmo, Clarice Tanaka, Julio F M Marchini, Thaís Guimarães, Ester Sabino, Carlos Roberto Ribeiro Carvalho, Celina Almeida Lamas, Diego Armando Cardona Cardenas, Daniel Mario Lima, Paula Gobi Scudeller, João Marcos Salge, Cesar Higa Nomura, Marco Antonio Gutierrez, Adriana L Araújo, Bruno F Guedes, Carolina S Lázari, Cassiano C Antonio, Claudia C Leite, Emmanuel A Burdmann, Euripedes C Miguel, Fabio R Pinna, Fabiane Y O Kawano, Geraldo F Busatto, Giovanni G Cerri, Heraldo P Souza, Izabel C Rios, Larissa S Oliveira, Linamara R Batisttella, Luiz Henrique M Castro, Marcello M C Magri, Maria Cassia J M Corrêa, Maria Cristina P B Francisco, Maura S Oliveira, Orestes V Forlenza, Ricardo F Bento, Rodolfo F Damiano, Rossana P Francisco, Solange R G Fusco, Tarcisio E P Barros-Filho, Wilson J Filho

“…Objective This study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection.Design This prospective cohort study included COVID-19 survivors hospitalised between 30 March 2020 and 31 August 2020 followed-up 6 months after hospital discharge. …”
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Predictive Modeling of Flood Frequency Utilizing an Analysis of the Casimcea River in Romania by Carmen Maftei, Constantin Cerneaga, Ashok Vaseashta

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Usage of Neural-Based Predictive Modeling and IIoT in Wind Energy Applications by Adrian-Nicolae Buturache, Stelian Stancu

“…The stochastic nature of wind speed is transferred to wind turbine output, making wind energy difficult to predict. The main scope of predicting wind energy production is to be proactive in balancing and reserving energy to meet demand. …”
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Hydraulic Erosion Rate of Reinforced Tailings: Laboratory Investigation and Prediction Model by Xuanyi Chen, Xiaofei Jing, Hai Cai, Yijun Wang, Luhua Ye

“…This model can provide a reference for the prediction of overtopping-induced erosion failure of the reinforced tailings dam.…”
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Comprehensive predictive model for cerebral microbleeds: integrating clinical and biochemical markers by Lijing Wang, Yao Li, Yadong Hu, Li Ling, Nan Jia, Yajing Chen, Yanan Meng, Ye Jiang, Ning Li

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Prediction Model of Music Popular Trend Based on NNS and DM Technology by Yichen Xu, Mingxun Wang, Hao Chen, Fan Hu

“…Therefore, it can be proved that the model proposed in this paper is more suitable for predicting the trend of music popularity. …”
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Significant Serpents: Predictive Modelling of Bioclimatic Venom Variation in Russell's Viper. by Navaneel Sarangi, R R Senji Laxme, Kartik Sunagar

“…Furthermore, predictive models were employed to map venom phenotypes across the distribution range of D. russelii.…”
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Employing the Coupled EUHFORIA‐OpenGGCM Model to Predict CME Geoeffectiveness by Anwesha Maharana, W. Douglas Cramer, Evangelia Samara, Camilla Scolini, Joachim Raeder, Stefaan Poedts

“…We further employ the dynamic time warping (DTW) technique to assess the model performance in predicting Dst. The main highlight of this study is to use EUHFORIA simulated time series to predict the Dst and auroral indices 1–2 days in advance, as compared to using the observed solar wind data at L1, which only provides predictions 1–2 hr before the actual impact.…”
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Feeding the machine: Challenges to reproducible predictive modeling in resting-state connectomics by Andrew Cwiek, Sarah M. Rajtmajer, Bradley Wyble, Vasant Honavar, Emily Grossner, Frank G. Hillary

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Depth prediction of urban waterlogging based on BiTCN-GRU modeling. by Quan Wang, Mingjie Tang, Pei Shi

“…Compared to models such as GBDT, LSTM, and TCN-LSTM, the BiTCN-GRU model exhibits higher accuracy in predicting waterlogging depth. …”
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Local Differential Privacy Graph Data Modeling Method for Link Prediction by HANQilong, WUXiaoming

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A lightweight hybrid model for accurate ammonia prediction in pig houses by Jacqueline Musabimana, Qiuju Xie, Hong Zhou, Ping Zheng, Honggui Liu, Tiemin Ma, Jiming Liu

“…The model improves accuracy compared to other state-of-the-art and ability for NH3 prediction.…”
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Risk Factors for Digital Replantation Failure: A Nomogram Prediction Model by Guo T, Ma T, Gao R, Yu K, Bai J

“…Then, we constructed a nomogram prediction model with 0.7538 in AUC of the prediction model with good consistency in the correction curve and good clinical practicality by decision curve analysis.Conclusion: The level of D-dimer and CRP was found to be closely related to DN. …”
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TBM shield mud cake prediction model based on machine learning by Qi Zhang, Peng Xu, Jing Zhang, Zhao Yang, Yu Li, Xintong Kong, Xiao Yuan

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LOGISTIC AND PROBIT REGRESSION MODELING TO PREDICT THE OPPORTUNITIES OF DIABETES IN PROSPECTIVE ATHLETES by Danang Ariyanto, A'yunin Sofro, A’idah Nur Hanifah, Junaidi Budi Prihanto, Dimas Avian Maulana, Riska Wahyu Romadhonia

“…This study aimed to develop an early prediction model for diabetes in prospective athletic candidates using a bivariate logistic and probit regression approach while considering the influence of socio-demographic and anthropometric factors. …”
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Lifestyle factors and colorectal cancer prediction: A nomogram-based model by Wooin Seo, Se Young Jung, Yeonhoon Jang, Kiheon Lee

“…This study developed and validated an age-based CRC risk-prediction model incorporating lifestyle factors using the National Health Insurance Service (NHIS)-National Sample Cohort database. …”
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Collaborative multiview time series modeling for vehicle maintenance demand prediction by Fanghua Chen, Deguang Shang, Gang Zhou, Ke Ye, Fujie Ren, Guofang Wu

“…To address these challenges, we propose an innovative method for predicting vehicle all maintenance demands based on collaborative multiview time series modeling. …”
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Cellular automata model based power network attack prediction technology by Lijuan YE, Yiting WANG, Licheng ZHU

Subjects: “…cellular automata;power network;attack probability;network information;prediction model…”
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