Improving Cardiovascular Disease Prediction through Stratified Machine Learning Models and Combined Datasets by Tara Yousif Mawlood, Alla Ahmad Hassan, Rebwar Khalid Muhammed, Aso M. Aladdin, Tarik A. Rashid, Bryar A. Hassan

“…The integration of datasets, stratified sampling, and k-fold validation effectively enhanced model reliability while minimizing overfitting. These findings highlight the potential of ML to support early CVD diagnosis and lay the groundwork for future research on hybrid models and real-world clinical applications.…”
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Performance Comparison of Prediction of Hydraulic Jump Length Under Multiple Neural Network Models by Ziyuan Xu, Zirui Liu, Yingzi Peng

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Health literacy prediction models based on machine learning methods: a scoping review by PAN Xiang, TONG Yingge, LI Yixuan, NI Ke, CHENG Wenqian, XIN Mengyu, HU Yuying

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The research of ARIMA, GM(1,1), and LSTM models for prediction of TB cases in China. by Daren Zhao, Huiwu Zhang, Qing Cao, Zhiyi Wang, Sizhang He, Minghua Zhou, Ruihua Zhang

“…The results showed that the LSTM was the optimal model, which can be achieved satisfactory performance for TB cases predictions in mainland China.…”
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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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Using resistor network models to predict the transport properties of solid-state battery composites by Lukas Ketter, Niklas Greb, Tim Bernges, Wolfgang G. Zeier

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Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models

“…In this study is predicted the groundwater level of Sharif Abad catchment using some artificial intelligence models. …”
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NeuroScale: evolutional scale-based protein language models enable prediction of neuropeptides by Hongqi Zhang, Shanghua Liu, Wei Su, Xueqin Xie, Junwen Yu, Fuying Dao, Mi Yang, Hao Lyu, Hao Lin

“…Results In this study, we introduce NeuroScale, a multi-channel neural network model leveraging evolutionary scale modeling (ESM) for the precise prediction of NPs. …”
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Construction and validation of risk prediction models for renal replacement therapy in patients with acute pancreatitis by Fei Zuo, Lei Zhong, Jie Min, Jinyu Zhang, Longping Yao

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How mathematical models might predict desertification from global warming and dust pollutants by Eman Hakeem, Shireen Jawad, Ali Hasan Ali, Mohamed Kallel, Husam A. Neamah

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Research on telecom industry customer churn prediction based on explainable machine learning models by WANG Shengjie, ZHANG Qinghong

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Genome‐scale models of metabolism and gene expression extend and refine growth phenotype prediction by Edward J O'Brien, Joshua A Lerman, Roger L Chang, Daniel R Hyduke, Bernhard Ø Palsson

“…Growth requirements are well‐characterized experimentally for many microbes; however, we lack a unified model for cellular growth. Such a model must be predictive of events at the molecular scale and capable of explaining the high‐level behavior of the cell as a whole. …”
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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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Efficient multi-station air quality prediction in Delhi with wavelet and optimization-based models. by Lakshmi Sankar, Krishnamoorthy Arasu

“…Precise and efficient prediction of air quality is essential for successful mitigation and policy formulation. …”
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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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TRIPOD statement: a preliminary pre-post analysis of reporting and methods of prediction models by Gary S Collins, Karel G M Moons, Lotty Hooft, Ewout W Steyerberg, Pauline Heus, Merel van Diepen, Friedo W Dekker, Amir H Zamanipoor Najafabadi, Chava L Ramspek, Wilco C Peul

“…Objectives To assess the difference in completeness of reporting and methodological conduct of published prediction models before and after publication of the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement.Methods In the seven general medicine journals with the highest impact factor, we compared the completeness of the reporting and the quality of the methodology of prediction model studies published between 2012 and 2014 (pre-TRIPOD) with studies published between 2016 and 2017 (post-TRIPOD). …”
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Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria by Sikiru Abdulganiyu Siyanbola, Aisha Olabisi Sowemimo, Zaid Habibu, Timothy Ebuka Eberechukwu

Subjects: “…flood prediction…”
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A Comparative Analysis of Deep Learning Models for Prediction of Microsatellite Instability in Colorectal Cancer by Ziynet Pamuk, Hüseyin Erikçi

“…This study proposes a deep learning-based model for predicting microsatellite instability (MSI) in colorectal cancer using hematoxylin and eosin (H&E)-stained histopathological tissue slides. …”
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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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Prediction rotary drilling penetration rate in lateritic soils using machine learning models by Eugène Gatchouessi Kamdem, Franck Ferry Kamgue Tiam, Luc Leroy Mambou Ngueyep, Olivier Wounabaissa, Hugues Richard Lembo Nnomo, Abraham Kanmogne

“…The present paper investigated an accurate machine learning model for the penetration rates (ROP) prediction in lateritic soil covers layers. …”
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