Predictive Models for Single-Droplet Ignition in Static High-Temperature Air in Different Gravity Environments by Xiaoyang Lan, Huilong Zheng, Yu Fang, Xianzhang Peng, Xiaofang Yang, Xiaowu Zhang

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AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models by Faruk Dikmen, Ahmet Demir, Bestami Özkaya, Muhammad Owais Raza, Jawad Rasheed, Tunc Asuroglu, Shtwai Alsubai

“…Abstract The integration of artificial intelligence (AI) in wastewater treatment management offers a promising approach to optimizing effluent quality predictions and enhancing operational efficiency. This study evaluates the performance of machine learning models in predicting key wastewater effluent parameters Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Total Suspended Solids (TSS), Total Effluent Nitrogen and Total Effluent Phosphorus. …”
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DNA methylation patterns and predictive models for metabolic disease risk in offspring of gestational diabetes mellitus by Na Wang, Suping Li, Li Yang

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The urban heat Island effect: A review on predictive approaches using artificial intelligence models by Ali Najah Ahmed, Nouar AlDahoul, Nurhanani A. Aziz, Y.F. Huang, Mohsen Sherif, Ahmed El-Shafie

“…While conventional ML algorithms remain widely used, DL and hybrid models have shown superior performance in predictive accuracy. …”
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A comprehensive review of predictive analytics models for mental illness using machine learning algorithms by Md. Monirul Islam, Shahriar Hassan, Sharmin Akter, Ferdaus Anam Jibon, Md. Sahidullah

“…This study reviews the machine learning models, algorithms, and applications for the early detection of mental disease, particularly emphasizing the data modalities. …”
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PERFORMANCE OF SIX PREDICTIVE MODELS OF DEATH OF PATIENTS HOSPITALIZED FOR DECOMPENSATED CIRRHOSIS: A MULTICENTER STUDY by Ajácio Bandeira de Mello BRANDÃO, Isadora Zanotelli BOMBASSARO, Gabriela Perdomo CORAL, Jonathan SOLDERA, Carlos KUPSKI

“…Several models have been developed and validated. Objective: To analyze and compare the performance of models in predicting 90-day mortality among patients hospitalized with decompensated cirrhosis. …”
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Author Correction: Advanced predictive machine and deep learning models for round-ended CFST column by Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy

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Challenges in developing reliable phosphorus predictive models: Unpredictable release under soil redox changes by Filippo Saiano, Riccardo Scalenghe

“…Nevertheless, we were unable to develop a predictive model for soil P desorption based on key intrinsic properties and climate. …”
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Predictive Artificial Intelligence Models for Energy Efficiency in Hybrid and Electric Vehicles: Analysis for Enna, Sicily by Maksymilian Mądziel, Tiziana Campisi

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Advancements in Predictive Maintenance: A Bibliometric Review of Diagnostic Models Using Machine Learning Techniques by Nontuthuzelo Lindokuhle Vithi, Colin Chibaya

“…This bibliometric review investigates the advancements in machine learning techniques for predictive maintenance, focusing on the use of Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) for fault detection in wheelset axle bearings. …”
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Antibody Fab‐Fc properties outperform titer in predictive models of SIV vaccine‐induced protection by Srivamshi Pittala, Kenneth Bagley, Jennifer A Schwartz, Eric P Brown, Joshua A Weiner, Ilia J Prado, Wenlei Zhang, Rong Xu, Ayuko Ota‐Setlik, Ranajit Pal, Xiaoying Shen, Charles Beck, Guido Ferrari, George K Lewis, Celia C LaBranche, David C Montefiori, Georgia D Tomaras, Galit Alter, Mario Roederer, Timothy R Fouts, Margaret E Ackerman, Chris Bailey‐Kellogg

“…These results suggest that predictive modeling with measurements of antibody properties can provide detailed correlates with robust predictive power, suggest directions for vaccine improvement, and potentially enable discovery of mechanistic associations.…”
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Creating simple predictive models in ecology, conservation and environmental policy based on Bayesian belief networks. by Victoria Dominguez Almela, Abigail R Croker, Richard Stafford

“…Predictive models are often complex to produce and interpret, yet can offer valuable insights for management, conservation and policy-making. …”
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Optimizing Apache Spark MLlib: Predictive Performance of Large-Scale Models for Big Data Analytics by Leonidas Theodorakopoulos, Aristeidis Karras, George A. Krimpas

“…The data were used to train predictive models that had up to 98% accuracy in forecasting performance. …”
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Depression screening model for middle-aged and elderly diabetic patients in China by Linfang Deng, Shaoting Luo, Tianyi Wang, He Xu

Subjects: “…Predictive model…”
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A nomogram model for predicting risk factors and the outcome of skin ulcer by Honglin Jia, Yang Tan, Hong Li, Xiaoqing Bu, Lingfei Li, Xia Lei

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Beyond Needling: Integrating a Bayesian Brain Model into Acupuncture Treatment by Beomku Kang, Da-Eun Yoon, Yeonhee Ryu, In-Seon Lee, Younbyoung Chae

“…Active inference from both prior experience and expectations of acupuncture, when integrated with incoming sensory signals, creates a unique, individual internal generative model of our perception of acupuncture. A Bayesian framework and predictive coding may, therefore, aid in elucidating and quantifying the cognitive components of acupuncture and facilitate understanding of their differential interactions in determining individual expectations of treatment. …”
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The TRIPOD Statement: how to present the results of diagnostic and prognostic studies by I. P. Kolos, D. A. Anichkov, S. A. Boytsov

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Muscle strength: development of predictive equation for handgrip strength in older adults on the primary health care by Maria Luiza Amorim Sena Pereira, Marília Conceição de Souza Caceres, Marlus Henrique Queiroz Pereira, Carolina Cunha de Oliveira, Bruno Klécius Andrade Teles, Elizabete Regina Araújo de Oliveira

“…This study aimed to develop equations for predicting HGS in community-dwelling older adults in Primary Health Care (PHC). …”
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Predicting customer subscription in bank telemarketing campaigns using ensemble learning models by Michael Peter, Hawa Mofi, Said Likoko, Julius Sabas, Ramadhani Mbura, Neema Mduma

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AdditiveLLM: Large language models predict defects in metals additive manufacturing by Peter Pak, Amir Barati Farimani

“…In this work we investigate the ability of large language models to predict additive manufacturing defect regimes given a set of process parameter inputs. …”
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