Development and validation of predictive models for meige syndrome patients based on oxidative stress markers by Yingjie Zhu, Runing Fu, Ziang Wang, Xinjie Zhu, Pengbo Feng, Xinyu Feng, Wenping Lian

“…The cross-validation confirmed the model’s reliability. The model demonstrated high predictive accuracy, with an area under the curve (AUC) of 0.930 for the training set and 0.914 for the validation set. …”
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Integrating radiomics into predictive models for low nuclear grade DCIS using machine learning by Yimin Wu, Daojing Xu, Zongyu Zha, Li Gu, Jieqing Chen, Jiagui Fang, Ziyang Dou, Pingyang Zhang, Chaoxue Zhang, Junli Wang

“…Our findings emphasize the importance of integrating Radiomic into DCIS prediction models, offering fresh perspectives for personalized treatment and clinical management of DCIS.…”
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A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems by Philomina Onyedikachi Peter, Edoardo Bertone, Rodney A. Stewart

“…Furthermore, it offers evidence-based recommendations for selecting appropriate models to predict ENT levels, empowering researchers and water resource managers to design more effective water quality management strategies. …”
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Advancing Predictive Healthcare: A Systematic Review of Transformer Models in Electronic Health Records by Azza Mohamed, Reem AlAleeli, Khaled Shaalan

“…The research questions focus on how these models can improve clinical decision-making through information extraction and predictive analytics. …”
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Predictive interpretable analytics models for forecasting healthcare costs using open healthcare data by A. Ravishankar Rao, Raunak Jain, Mrityunjai Singh, Rahul Garg

“…We demonstrate our approach by creating predictive models using recent machine learning techniques. …”
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Predictive models for the surface roughness and subsurface damage depth of semiconductor materials in precision grinding by Shang Gao, Haoxiang Wang, Han Huang, Zhigang Dong, Renke Kang

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Optimized machine learning based comparative analysis of predictive models for classification of kidney tumors by Vatsala Anand, Ajay Khajuria, Rupendra Kumar Pachauri, Vinay Gupta

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Predictive Performance Evaluation of ARIMA and Hybrid ARIMA-LSTM Models for Particulate Matter Concentration by Johanes Dian Kurniawan, Hanna Arini Parhusip, Suryasatria Trihandaru

“…This study provides an objective evaluation of prediction performance models for particulate matter policy for industrial stakeholders by comparing the ARIMA and Hybrid ARIMA-LSTM models for predicting air quality data from the industrial environment. …”
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Extended sample size calculations for evaluation of prediction models using a threshold for classification by Rebecca Whittle, Joie Ensor, Lucinda Archer, Gary S. Collins, Paula Dhiman, Alastair Denniston, Joseph Alderman, Amardeep Legha, Maarten van Smeden, Karel G. Moons, Jean-Baptiste Cazier, Richard D. Riley, Kym I. E Snell

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ParaAntiProt provides paratope prediction using antibody and protein language models by Mahmood Kalemati, Alireza Noroozi, Aref Shahbakhsh, Somayyeh Koohi

Subjects: “…Paratope prediction…”
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A comparative analysis of classical machine learning models with quantum-inspired models for predicting world surface temperature by Trilok Nath Pandey, Vishvajeet Ravalekar, Sidharth D. Nair, Sunil Kumar Pradhan

“…As the amount and complexity of time-series data in numerous fields continues to expand, the investigation of advanced computational models becomes critical for efficient analysis and prediction. …”
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Construction of Machine Learning Models to Predict the Maximum Absorption Wavelength Considering the Solute and Solvent and Inverse Analysis of the Models by Haruki Ochiai, Hiromasa Kaneko

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Heuristic modeling of the process of milling aviation parts with opposed end mills by synthesis of a predictive model by E. A. Shestakova, V. O. Ievlev, R. M. Yanbaev

“…The resulting model allows predicting the results of machining by the proposed method with an error of 10…15%.…”
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Modeling and control of automatic voltage regulation for a hydropower plant using advanced model predictive control by Ebunle Akupan Rene, Willy Stephen Tounsi Fokui

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To What Extent Does Discounting ‘Hot’ Climate Models Improve the Predictive Skill of Climate Model Ensembles? by Abigail McDonnell, Adam Michael Bauer, Cristian Proistosescu

“…The Intergovernmental Panel on Climate Change's (IPCC) Assessment Report Six (AR6) took a step toward ending so‐called ‘model democracy’ by discounting climate models that are too warm over the historical period (i.e., models that ‘run hot’) when making projections of global temperature change. …”
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Temporal trends and predictive modeling of air pollutants in Delhi: a comparative study of artificial intelligence models by Omer A. Alawi, Haslinda Mohamed Kamar, Ali Alsuwaiyan, Zaher Mundher Yaseen

“…The modelling results revealed that Bi-LSTM model had the best predictability performance for forecasting CO with (R2 = 0.979), NO with (R2 = 0.961), NO2 with (R2 = 0.956), SO2 with (R2 = 0.955), PM10 with (R2 = 0.9751) and NH3 with (R2 = 0.971). …”
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Generalization of a fast, predictive model for tokamak scenario design in ASTRA and comparison to a RAPTOR model by Raphael Schramm, Alexander Bock, Emiliano Fable, Jörg Stober, Simon van Mulders, Marc Maraschek, Rainer Fischer, Andreas Burckhart, Philip Schneider, Olivier Sauter, Hartmut Zohm, the ASDEX Upgrade Team, JET Contributors

“…We have previously presented an analytical predictive model to aid in the AT scenario design, optimized for a single scenario (Schramm et al 2024 Nucl. …”
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A hybrid workflow connecting a network and an agent-based model for predictive pedestrian movement modelling by Anita Ullrich, Franziska Hunger, Ioanna Stavroulaki, Adam Bilock, Klas Jareteg, Yury Tarakanov, Alexander Gösta, Alexander Gösta, Johannes Quist, Meta Berghauser Pont, Fredrik Edelvik

“…This study outlines a comprehensive workflow tailored for urban planners. It proposes a hybrid model that integrates an agent-based model, which simulates the micro-scale movement of pedestrians in outdoor urban environments, with a network model, which predicts the aggregated pedestrian flows on a macro-scale. …”
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EVALUATION OF THE RELATIONSHIP BETWEEN SPRAY LIQUID PRESSURE AND MACHINE SPEED USING THREE TYPES OF NOZZLES ON A BOOM SPRAYER by G. Tihanov, G. Hristova, P. Veleva

Subjects: “…sprayers, nozzles, working pressure, operational speed, predictive models.…”
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Development and validation of a gut motility based model for predicting bowel preparation quality by Hongjiao Wu, Rui Wu, Yunyun Zhang, Xinyi Lu, Wei Zhao, Biyun Xu, Jun Liu, Nina Zhang

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