PREDICTION STAGES OF THE DIFFICULT INERTIA SYSTEM BEHAVIOR WITH THE USE OF THE DEVELOPED SYSTEM MODEL by Vasyl V. Bychenkov

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Prediction of power grid fault repair time based on multi-model fusion by Jianyue PAN, Yizhen WU, Hanlin XU

“…There are many types of power grid faults,and the reasons are complicated.The prediction of fault repair time is difficult.Due to the rise of new technologies such as deep learning,it is feasible to accurately mine the faulty worksheet and accurately predict the fault repair time.Taking the historical grid fault repair worksheet as the research object,the multi-model fusion prediction method was proposed,and the prediction results of LightGBM,XGBoost and LSTM were weighted and fused.The experimental results show that the multi-model fusion prediction method can accurately estimate the fault repair time and provide better support for the automation and intelligence of grid fault repair.…”
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Large language model trained on clinical oncology data predicts cancer progression by Menglei Zhu, Hui Lin, Jue Jiang, Abbas J. Jinia, Justin Jee, Karl Pichotta, Michele Waters, Doori Rose, Nikolaus Schultz, Sulov Chalise, Lohit Valleru, Olivier Morin, Jean Moran, Joseph O. Deasy, Shirin Pilai, Chelsea Nichols, Gregory Riely, Lior Z. Braunstein, Anyi Li

“…Abstract Subspecialty knowledge barriers have limited the adoption of large language models (LLMs) in oncology. We introduce Woollie, an open-source, oncology-specific LLM trained on real-world data from Memorial Sloan Kettering Cancer Center (MSK) across lung, breast, prostate, pancreatic, and colorectal cancers, with external validation using University of California, San Francisco (UCSF) data. …”
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AI Knows You: Deep Learning Model for Prediction of Extroversion Personality Trait by Anam Naz, Hikmat Ullah Khan, Sami Alesawi, Omar Ibrahim Abouola, Ali Daud, Muhammad Ramzan

“…The state-of-the-art shallow machine learning, ensemble modelling and deep learning models are applied. The main novelty is the exploration of latest sentence embeddings which captures semantic information of content in a better manner. …”
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Penalized Logistic Regression Models for Phenotype Prediction Based on Single Nucleotide Polymorphisms by seyedeh rezwan Hosseini, Farnaz Ghassemi, Mohammad Hasan Moradi

“…Some SNPs alone and some by interacting with others, play an important role in any phenotype or specific disease. Various models, including the regression models, are designed and implemented for the prediction of these diseases. …”
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PREDICT LEARNERS’ PERFORMANCE USING AN ONTOLOGICAL-BASED MODEL ON AN E-LEARNING PLATFORM by Safa Ridha Albo Abdullah

“…In learning analytics and educational data mining, a prominent challenge is posed by the lack of portability and transferability of predictive models across different courses. A novel ontology-based decision tree model is introduced in this study, which significantly enhances portability by incorporating semantic features. …”
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Thermal Performance of Lightweight Earth: From Prediction to Optimization through Multiscale Modeling by Séverine Rosa Latapie, Vincent Sabathier, Ariane Abou-Chakra

“…Mean-field homogenization techniques, including the Mori-Tanaka as well as double inclusion models, are used to develop predictive tools for thermal behavior, using rigorously selected experimental data. …”
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A Robust Hybrid CNN–LSTM Model for Predicting Student Academic Performance by Kuburat Oyeranti Adefemi, Murimo Bethel Mutanga

“…However, many existing models struggle with generalizability and fail to effectively manage data challenges such as class imbalance and missing data, leading to suboptimal predictive performance. …”
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Fast and effective assessment for individuals with special needs form optimization and prediction models by Bilal Baris Alkan, Muhammet Kumartas, Serafettin Kuzucuk, Nesrin Alkan

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Predicting the Evolution of Shallow Cumulus Clouds With a Lotka‐Volterra Like Model by Jingyi Chen, Samson Hagos, Jerome Fast, Zhe Feng

“…Abstract In numerical weather prediction and climate models, boundary‐layer clouds are controlled by a wide range of subgrid‐scale processes. …”
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Prediction models for intraventricular hemorrhage in very preterm infants: a systematic review by Ping Xiong, Yonggang Wei, Lei Li, Houxin Kang, Zhangbin Yu, Hong Tang, Yuanlin Pu

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Construction of a disease risk prediction model for postherpetic pruritus by machine learning by Zheng Lin, Yuan Dou, Ru-yi Ju, Ping Lin, Yi Cao

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Dynamic in-context learning with conversational models for data extraction and materials property prediction by Chinedu E. Ekuma

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Risk prediction model for waitlist mortality in patients with left ventricular assist devices by Anjan Tibrewala, MD, MS, Duc Thinh Pham, MD, Mo Hu, MS, Lucia C. Petito, PhD, Jonathan D. Rich, MD, Finn Gustafsson, MD, PhD, Theo M.M.H. de By, MBA, PhD, Kevin Veen, MD, PhD, Donald M. Lloyd-Jones, MD, ScM, Sanjiv J. Shah, MD

“…We sought to derive and validate a risk prediction model for waitlist mortality in LVAD patients. …”
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Numerically predicting deflections of mat-sand interaction model under gravity loadings by Md. Foisal Haque, Nure Ashraf, Jahidul Islam Chalkder, Abu Salem Musa

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Time series analysis for modeling and predicting confirmed cases of influenza a in Algeria by Djillali Seba, N. Benaklef, K. Belaide

“…This study employed a comprehensive approach to develop a model for predicting confirmed cases of Influenza A in Algeria. …”
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Rainfall‐Runoff Modeling in Rocky Headwater Catchments for the Prediction of Debris Flow Occurrence by Martino Bernard, Matteo Barbini, Matteo Berti, Mauro Boreggio, Alessandro Simoni, Carlo Gregoretti

“…These findings suggest that a well‐tuned hydrological model can predict the discharge from intense, short rainfall events that typically trigger debris flows, as well as the early stages of these phenomena.…”
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Prediction Model of Interval Grey Numbers with a Real Parameter and Its Application by Bo Zeng, Chuan Li, Xue-Yu Zhou, Xian-Jun Long

“…Grey prediction models have become common methods which are widely employed to solve the problems with “small examples and poor information.” …”
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…Wind field forecast is of great significance for aerostat trajectory prediction. Traditional theoretical models can only predict wind speed in the next few hours, while BP neural network models can predict wind speeds in next few days. …”
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Artificial intelligence prediction models for acute respiratory distress syndrome：progress and challenges by MENG Xianglin*，XIONG Yaxin，HAN Ci，GE Xin，ZHAO Mingyan

“…Compared with traditional scoring systems，AI models perform well in predicting mortality and optimizing clinical decision ⁃ making，especially through multimodal data fusion，which can significantly improve the prediction accuracy of the models. …”
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