Machine Learning Methods for Evaluation of Technical Factors of Spraying in Permanent Plantations by Vjekoslav Tadić, Dorijan Radočaj, Mladen Jurišić

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ECONOMETRIC METHODS IN FORECAST EVALUATION OF THE DEVELOPMENT STRATEGY OF A MANUFACTURING SYSTEM by A. N. Mardas, O. A. Gulyaeva

“…The article is devoted to the problem of predictive evaluation of the development strategy efficiency of a manufacturing system under non-stationary conditions. …”
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Comparative Study on Performance Evaluation of Eager versus Lazy Learning Methods by Selvi Lukman, Jimmy Loekito, Pin Panji Yapinus

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Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method by Fachri Ayudi Fitrony, Laksmita Dewi Supraba, Tessa Rantung, I Made Artha Agastya, Kusrini Kusrini

“…This study aims to evaluate the historical pattern of new student admissions at UNU Pasuruan and predict the number of new students in the coming years using the ARIMA (Auto Regressive Integrated Moving Average) method. …”
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An evaluation methodology for machine learning-based tandem mass spectra similarity prediction by Michael Strobel, Alberto Gil-de-la-Fuente, Mohammad Reza Zare Shahneh, Yasin El Abiead, Roman Bushuiev, Anton Bushuiev, Tomáš Pluskal, Mingxun Wang

“…Machine learning (ML) approaches have emerged as a promising technique to predict structural similarity from MS/MS that may surpass the current state-of-the-art algorithmic methods. …”
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Economic Evaluation of the Investment in Sensor Equipment Based on Data Valuation in Prediction Model by Jeong-Gi Lee, Deok-Joo Lee

“…Traditional approaches primarily address this problem from a performance-oriented perspective, focusing on metrics like prediction or estimation accuracy. However, these methods often overlook the economic value that sensors can contribute. …”
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Evaluation of mathematical models for predicting medicine distribution into breastmilk - considering biological heterogeneity by Sumin Heo, Sumin Heo, Andrew S. Butler, Marina Stamouli Simoncioni, Sam Moult, Maria Malamatari, Essam Kerwash, Susan Cole

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Hospital-wide, dynamic, individualized prediction of central line-associated bloodstream infections-development and temporal evaluation of six prediction models by Elena Albu, Shan Gao, Pieter Stijnen, Frank E. Rademakers, Christel Janssens, Veerle Cossey, Yves Debaveye, Laure Wynants, Ben Van Calster

“…Aim To develop and temporally evaluate dynamic prediction models for continuous CLABSI risk monitoring. …”
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Prediction of 1-year post-operative mortality in elderly patients with fragility hip fractures in China: evaluation of risk prediction models by Qiyuan Lu, Mengmeng Chen, Houfu Ling

“…This investigation conducts a comparative evaluation of seven prognostic models—the Sernbo Score, Jiang et al. model, Nottingham Hip Fracture Score (NHFS), Holt et al. algorithm, HEMA, ASAgeCoGeCC Score, and SHiPS—HiPSe, and SHire, and SHim, HEMA, ham Hip Fracture Score (mortality risk prediction in elderly fragility hip fracture patientsMethodsIn this retrospective cohort analysis, all consecutive patients aged isk prediction in elderly fragility hip fracture between January 2018 and October 2022 were enrolled. …”
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Feasibility of predicting firearm type in firearm suicide deaths for better policy evaluation by Emma L. Gause, Alice M. Ellyson, Ali Rowhani-Rahbar

“…Methods An 80% training set of NDVRS data (2005–2018; 40 states and D.C.) was fit to candidate models (logistic regression, C5, and random forest) to predict long gun vs. handgun use in firearm suicide deaths. …”
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Predicting and evaluating slope stability in permafrost regions of the central Qinghai‒Tibetan Plateau by Fei Wang, Bo Huang, Mikhail Zhelezniak, Xiao-Ying Li, Alexander Zhirkov, Qi-Hao Yu, Zhi Wen

“…However, there have been no adequate methods to predict thermokarst landslides until now. …”
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Angiopoietin-like4 can be used to evaluate and predict efficacy for membranous nephropathy by WANG Jian, NING Li, WANG Run-xiu, CAO Feng

“…Objective To investigate the feasibility of serum and urine angiopoietin-like 4(Angptl4) for evaluating and predicting efficacy for membranous nephropathy. …”
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Machine learning prediction of ammonia nitrogen adsorption on biochar with model evaluation and optimization by Chong Liu, Paramasivan Balasubramanian, Jingxian An, Fayong Li

“…Twelve ML models, including tree-based ensembles, kernel-based methods, and deep learning, were evaluated using Bayesian optimization and cross-validation. …”
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The role of financial analysis in evaluating the performance of industrial enterprises to predict financial failure by Talal AL- Kassar, Mourad Kouachi, Ammar Nasruldeen

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A Review of Wind Power Prediction Methods Based on Multi-Time Scales by Fan Li, Hongzhen Wang, Dan Wang, Dong Liu, Ke Sun

“…Common classification angles of wind power prediction methods are outlined. By synthesizing existing approaches through multi-time scales, from the ultra-short term and short term to mid-long term, the review further deconstructs methods by model characteristics, input data types, spatial scales, and evaluation metrics. …”
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Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments by Liangtao Xu, Shuang Chen, Wen Yao

“…The numerical forecast results were evaluated using the neighborhood-based equitable threat score (ETS) and fraction skill score (FSS) verification methods based on nationwide observational lightning data. …”
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Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations by Badriah Alkalifah, Muhammad Tariq Shaheen, Johrah Alotibi, Tahani Alsubait, Hosam Alhakami

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Evaluating risk stratification scoring systems to predict mortality in patients with COVID-19 by Naveen Garg, Kelly Chu, Batool Alharahsheh, Payal Guha

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Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities by Paul Iacobescu, Virginia Marina, Catalin Anghel, Aurelian-Dumitrache Anghele

“…Early detection and diagnosis of CVD can significantly reduce the risk of complications and mortality. Machine learning methods, particularly classification algorithms, have demonstrated their potential to accurately predict the risk of cardiovascular disease (CVD) by analyzing patient data. …”
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AI-driven fall risk prediction in inpatients: Development, validation, and comparative evaluation by Chia-Lun Lo, Chia-En Liu, Hsiao Yun Chang, Chiu-Hsiang Wu

“…This study developed an AI-based fall risk prediction model using supervised learning techniques to enhance predictive accuracy and clinical integration. …”
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