Machine Learning Predictive Models for Survival in Patients with Brain Stroke by Solmaz Norouzi, Samira Ahmadi, Shayeste Alinia, Farshid Farzipoor, Azadeh Shahsavari, Ebrahim Hajizadeh, Mohammad Asghari Jafarabadi

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Development and Validation of Predictive Models for Non-Adherence to Antihypertensive Medication by Cristian Daniel Marineci, Andrei Valeanu, Cornel Chiriță, Simona Negreș, Claudiu Stoicescu, Valentin Chioncel

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Predictive Control of Mobile Robot Using Kinematic and Dynamic Models by Manel Mendili, Faouzi Bouani

“…Two predictive controllers are developed. The first is based on the kinematic model and the second is founded on the dynamic model. …”
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Recent advances in explainable Machine Learning models for wildfire prediction by Abira Sengupta, Brendon J. Woodford

“…Machine Learning (ML) and Artificial Intelligence models have emerged to predict both the onset of wildfires and evaluate the extent of damage a wildfire would cause. …”
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Prediction of hepatitis-C virus using statistical learning models by Shalini Kumari, Subhajit Das, Prashant Kumar Sonker, Agni Saroj, Mukesh Kumar

“…The models were evaluated using various performance metrics, and a comparative analysis using non-parametric tests was conducted to evaluate the statistical significance of the model. …”
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Processing and Shelf-Life Prediction Models for Ready-to-Eat Crayfish by Qian Li, Jieyu Lei, Keying Su, Xiaoying Chen, Laihoong Cheng, Chunmin Yang, Shiyi Ou

“…This study investigated the production process of ready-to-eat crayfish, focusing on changes in sensory quality, pH, total volatile base nitrogen (TVB-N), total viable count (TVC), acid value (AV), springiness, and hardness during storage at 4 °C, 25 °C, and 37 °C. A shelf-life prediction model was developed using the Arrhenius model. …”
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Zero-Shot Prediction of Conversational Derailment With Large Language Models by Kenya Nonaka, Mitsuo Yoshida

“…First, we measured the performance of the most commonly used LLMs in predicting conversational derailments and found that the zero-shot prediction performance is comparable to that of traditional fine-tuning approaches. …”
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Predictive models for concrete strength estimation of existing bridges in Brazil by Matheus Sant’Anna Andrade, Diôgo Silva de Oliveira, Letícia Negris Gardioli, Carol Ferreira Rezende Santos, José Carlos Lopes Ribeiro, José Maria Franco de Carvalho, Kléos Magalhães César Lenz Junior

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SYNTHESIS OF ECONOMETRIC AND NEURAL NETWORK MODELS FOR INDICATORS PREDICTION IN RESEARCH AND INNOVATION IN THE RUSSIAN FEDERATION by I. Kolmakov, M. Domozhakov

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Model for Reliability Prediction of Thick Film Resistors by D. S. Campbell, R. B. Pranchov

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A multimodal model for protein function prediction by Yu Mao, WenHui Xu, Yue Shun, LongXin Chai, Lei Xue, Yong Yang, Mei Li

Subjects: “…Protein function prediction…”
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Model for non-periodic time series prediction by CAO Jianwen, WEI Xingbao, YANG Yi, LI Caihong, ZHAO Wenqing

“…To effectively forecast non-periodic time series, the ILTNet model was proposed based on the Informer model. The ILTNet model integrated linear prediction (AR model) and nonlinear prediction (Informer model and recurrent skip components), enabling effective capture of long-term dependencies. …”
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STVMamba: precipitation nowcasting with spatiotemporal prediction model by Maoyang Zou, Longrui Wen, Yuanyuan Huang, Yuan He, Jingzhong Xiao

“…Deep learning methods such as recurrent, convolutional, and Transformer models have been applied to precipitation prediction. …”
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Prediction Model of Pipeline Push Resistance in Tunnels by Lianmin Cao, Mingxing Zhu, Dekang Zhang, Ying Zhen, Xu Zhang, Yuguang Cao

“…Accurate determination of pipeline push resistance and the selection of an appropriate pipe pusher model are crucial factors for successful construction. …”
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Research on Simplified Design of Model Predictive Control by Qing Zhang, Chi Zhang, Qi Wang, Shiyun Dong, Aoqi Xiao

Subjects: “…model predictive control…”
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Fuzzy Model Predictive Control for Unmanned Helicopter by Łukasz Kiciński, Sebastian Topczewski

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Modeling and Prediction of Ride-Sharing Utilization Dynamics by Tal Altshuler, Yaniv Altshuler, Rachel Katoshevski, Yoram Shiftan

“…This feature space is then used to model the dynamics of ride-sharing utilization over time. …”
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Editorial: Model organisms in predictive toxicology 2023 by Cristina Luceri, Abdulahad Dogan, Angel León-Buitimea

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Air Quality Prediction Model for Monitoring AQI by Das Aritra, Gupta Himanshu

“…This research proposes a complete framework that incorporates deep learning models—specifically Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) networks—with ensemble learning methods, particularly Extreme Gradient Boosting (XGBoost), to predict AQI. …”
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Macroscopic Modelling of Predicted Automated Vehicle Emissions by Mohammed Obaid, Arpad Torok

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