Advancing wastewater reuse: AI-driven insights into ozone-based organic pollutant reduction by Syed Muzzamil Hussain Shah, Sani I. Abba, Mohamed A. Yassin, Ebrahim Al-Qadami, Dahiru U. Lawal, Imtiaz Afzal Khan, Jamilu Usman, Haris U. Qureshi, Isam H. Aljundi

“…Subsequently, the study further integrated Artificial Intelligence (AI) assisted Machine Learning (ML) for accurate ORP prediction. …”
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Artificial intelligence for surgical outcome prediction in glaucoma: a systematic review by Zeena Kailani, Lauren Kim, Joshua Bierbrier, Michael Balas, David J. Mathew, David J. Mathew

“…A variety of algorithms were applied, including random forests, support vector machines, and neural networks. Overall, AI models consistently outperformed traditional statistical approaches, with the best-performing model achieving an accuracy of 87.5%. …”
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Order Management in the Era of Customization by A. V. Netievsky, M. A. Prilutskaya

“…In the current conditions, mechanical engineering enterprises increasingly need to adapt to each individual customer, which in turn forces them to rebuild enterprises to the parameters typical for single or small-scale production. …”
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INTEGRATING ACOUSTIC MODULATION AND LISTENER DEMOGRAPHICS FOR ENHANCED PODCAST EMOTIONAL RESONANCE by Jun Ji, Kotchaphan Youngmee, Khachakrit Liamthaisong, Narisara Brikshavana

“…The underlying framework combines analytical methods, computational modelling, and machine learning in order to systematically enhance audio quality and consequently increase listener engagement.  …”
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Ta-YOLO: overcoming target blocked challenges in greenhouse tomato detection and counting by Yun Zhao, Yijia Chen, Xing Xu, Yong He, Hao Gan, Na Wu, Zhechen Wang, Xi Sun, Yali Wang, Petr Skobelev, Yanan Mi

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Predictive analytics technique based on hybrid sampling to manage unbalanced data in smart cities by Ayushi Chahal, Preeti Gulia, Nasib Singh Gill, Mohammad Yahya, Mohd Anul Haq, Mohammed Aleisa, Abdullah Alenizi, Arfat Ahmad Khan, Piyush Kumar Shukla

“…A pipeline is designed using Principal Component Analysis (PCA), a hybrid sampling method, and a Machine Learning (ML) prediction method. SMOTE + ENN, a hybrid data balancing method, is used to specify imbalanced data to a balanced state. …”
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Development and validation of a novel public prediction platform for deciduous caries in preschool children: an observational study from Northwest China by Zhidong Zhang, Zhihao Dou, Xu Zhang, Di Wang, Kamenjiang Abudoureheman, Yimin Yan, Fenyan Kang, Wei Zhang, Wenbo Meng, Kailiang Zhang, Zhige Li, Jie Zhang, Bin Liu, Baoping Zhang

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AI may help to predict thyroid nodule malignancy based on radiomics features from [18F]FDG PET/CT by Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek

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Development and validation of a predictive model for invasive ventilation risk within 48 hours of admission in patients with early sepsis-associated acute kidney injury by Li Hong, Bin Wang

“…Variables included age, blood parameters, and vital signs at admission. Patients were divided into training and validation cohorts. …”
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Analysis of LULC Change Dynamics That Have Occurred in Tuscany (Italy) Since 2007 by Lorenzo Arcidiaco, Manuela Corongiu

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A Seq-to-Seq Temporal Convolutional Network for Volleyball Jump Monitoring Using a Waist-Mounted IMU by Meng Shang, Camilla de Bleecker, Jos Vanrenterghem, Roel de Ridder, Sabine Verschueren, Carolina Varon, Walter de Raedt, Bart Vanrumste

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Gated-LNN: Gated Liquid Neural Networks for Accurate Water Quality Index Prediction and Classification by Sreeni Chadalavada, Suleyman Yaman, Abdulkadir Sengur, Abdul Hafeez-Baig, Ru-San Tan, Prabal Datta Barua, Ravinesh C. Deo, Makiko Kobayashi, U. Rajendra Acharya

“…The dataset comprises seven most significant parameters of water quality, i.e., dissolved oxygen, pH, conductivity, biological oxygen demand, nitrate, fecal coliform, and total coliform. …”
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Annotated image dataset with different stages of European pear rust for UAV-based automated symptom detection in orchardsMendeley Data by Virginia Maß, Pendar Alirezazadeh, Johannes Seidl-Schulz, Matthias Leipnitz, Eric Fritzsche, Rasheed Ali Adam Ibraheem, Martin Geyer, Michael Pflanz, Stefanie Reim

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Integrating Artificial Neural Network-PROSAIL With Sentinel-2 to Monitor Crop Traits Dynamics and Nitrogen Status by Jose Luis Pancorbo, Miguel Quemada, Maria Dolores Raya-Sereno, Beniamino Gioli, Pieter S. A. Beck, Carlos Camino

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Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics by Zhenze Zhang, Zhenze Zhang, Caiqing Zhao, Caiqing Zhao, Yijun Zhou, Ling Yao, Peng Liu, Ziling Fang, Nian Fang, Nian Fang

“…Predictors included demographics, comorbidities, laboratory parameters, vital signs, and disease severity scores. …”
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Data-driven thrust prediction in applied-field magnetoplasmadynamic thrusters for space missions using artificial intelligence-based models by Tarik Pinaffo Almeida, Shahin Alipour Bonab, Mohammad Yazdani-Asrami

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DWE: Research on Water Quality Inversion and Scalability in Small Watersheds Using UAV Remote Sensing Data by Hao Li, Zhijun Xie, Xing Jin, Changchun Peng, Cheng Ren, Yunfei Mao, Kefan Zhou, Yingying Li

“…Therefore, this study applies the idea of integrated modeling to remote sensing inversion of water quality parameters (WQPs), and proposes an adaptive dynamic weighted ensemble learning (DWE) model, aiming to integrate the advantages of different machine learning models, improve the accuracy of WQP inversion, and adaptively assign dynamic weights to different machine learning models, thereby achieving the scalability of the model in time and space. …”
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Lymphocyte Inhibition Mechanisms and Immune Checkpoints in COVID-19: Insights into Prognostic Markers and Disease Severity by Martina Schniederova, Anna Bobcakova, Marian Grendar, Adam Markocsy, Andrej Ceres, Michal Cibulka, Dusan Dobrota, Milos Jesenak

“…However, it is essential to evaluate complex immune parameters in conjunction with other key clinical and laboratory indicators.…”
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A Bayesian Optimization Approach for Tuning a Grouping Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems by Cornelius Rüther, Julia Rieck

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Developing A Digital Twin of a TRUEX Extraction Process that Enables Non-proliferation and Safeguards Monitoring through Optical Spectroscopy and Machine Learning [version 1; peer... by Justin T. Cooper, Ramedy Flores, Addyson Barnes, Eduardo Trevino, Kathrine Jesse, Kolton Heaps, Adam J. Pluth, Ashley Shields, Jaren Brownlee

“…The separation efficiency of the process is dependent on a variety of parameters such as acid concentration, organic to aqueous (O/A) volume ratio, number of separation stages, etc. …”
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