Rheological behavior of MWCNT-SnO2/SAE50 hybrid nanolubricant: Experimental evaluation and viscosity prediction using optimized machine learning model by Mojtaba Sepehrnia, Hamid Maleki, Alireza Hamidi, Ali Davoodi, Hamidreza Golmohammadi

“…The proposed MLPNN optimization strategy, through the optimal selection of parameters such as the number of neurons of hidden layers (HLs), transfer functions of HLs, the transfer function of the output layer, and the training algorithm, provided significant efficiency in developing single HL (R2 = 0.99979) and double HLs (R2 = 0.99996) MLPNN models.…”
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Wound imaging software and digital platform to assist review of surgical wounds using patient smartphones: The development and evaluation of artificial intelligence (WISDOM AI stud... by Melissa Rochon, Judith Tanner, James Jurkiewicz, Jacqueline Beckhelling, Akuha Aondoakaa, Keith Wilson, Luxmi Dhoonmoon, Max Underwood, Lara Mason, Roy Harris, Karen Cariaga

“…<h4>Methods and analysis</h4>Conducted from September 2023 to March 2024, the study phases included compiling a training dataset of 37,974 images, creating a testing set of 3,634 images, developing an AI algorithm using 'You Only Look Once' models, and conducting prospective tests compared against clinical nurse specialists' evaluations. …”
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A differential diagnostic model based on immunological evaluation and routine laboratory tests: distinguishing multiple myeloma from other disorders with aberrant immunoglobulin el... by Manning Li, Sixun Jia, Han Wu, Chunyi Shou, Xiaolu Song, Ye Peng, Huafang Wang, Ying Wang, Xiangmin Tong, Yirui Chen

“…A discriminative diagnostic model was developed using a multivariate logistic regression algorithm. The model’s predictive accuracy and generalizability were evaluated by validating and conducting receiver operating characteristic (ROC) curves and calibration curves. …”
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Constitutive Model for Hot Deformation Behavior of Fe-Mn-Cr-Based Alloys: Physical Model, ANN Model, Model Optimization, Parameter Evaluation and Calibration by Jie Xu, Chaoyang Sun, Huijun Liang, Lingyun Qian, Chunhui Wang

“…Subsequently, traditional mathematical derivations and numerical optimization methods are evaluated. The parameters and architecture of the ANN model are then systematically optimized using optimization algorithms to enhance training efficiency and prediction accuracy. …”
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Privacy-Aware Detection for Large Language Models Using a Hybrid BiLSTM-HMM Approach by Maryam Abbasalizadeh, Sashank Narain

“…Additionally, the generated model trained on patterns derived from synthetic data, achieved <inline-formula> <tex-math notation="LaTeX">$\approx 99.99$ </tex-math></inline-formula>% accuracy when evaluated on a real-world dataset across varying sentence structures, demonstrating strong generalizability in detecting sensitive information regardless of the data source. …”
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HP_FLAP: homomorphic and polymorphic federated learning aggregation of parameters framework by Mohammad Moshawrab, Mehdi Adda, Abdenour Bouzouane, Hussein Ibrahim, Ali Raad

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Volcanic Activity Classification Through Semi-Supervised Learning Applied to Satellite Radiance Time Series by Francesco Spina, Giuseppe Bilotta, Annalisa Cappello, Marco Spina, Francesco Zuccarello, Gaetana Ganci

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Proposing a framework for body mass prediction with point clouds: A study applied in typical swine pen environments by Gabriel Pagin, Luciane Silva Martello, Rubens André Tabile, Rafael Vieira de Sousa

“…Subsequently, machine learning models (Random Tree - RT, Random Forest - RF, Linear Regression - LR, K-Nearest Neighbors - KNN, Support Vector Regression - SVR, and Multilayer Perceptron - MLP) were trained, optimized, and evaluated using k-fold cross-validation, followed by statistical analysis. …”
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Evaluating the value of machine learning models for predicting hematoma expansion in acute spontaneous intracerebral hemorrhage based on CT imaging features of hematomas and surrou... by Tianyu Yang, Tianyu Yang, Zhen Zhao, Yan Gu, Shengkai Yang, Yonggang Zhang, Lei Li, Ting Wang, Zhongchang Miao

“…Patients were divided into training (n = 128) and testing (n = 55) sets in a 7:3 ratio. …”
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College psychological stress assessment system based on LabVIEW and WTA integration by Ting Wang

“…The experimental results show that during the iterative training process, the training error of the research algorithm reaches 10–5 at the 200th iteration. …”
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Association of weight-adjusted waist index and body mass index with chronic low back pain in American adults: a retrospective cohort study and predictive model development based on... by Weiye Zhang, Weiye Zhang, Yan Li, Pengwei Shao, Yuxuan Du, Ke Zhao, Jiawen Zhan, Lee A. Tan

“…Subsequently, permutation feature importance was applied for machine learning feature selection, random undersampling was utilized to address data imbalance, and the dataset was randomly divided into training and testing sets at a 7:3 ratio. Six machine learning algorithms were employed to predict CLBP occurrence and identify the optimal algorithm.ResultsA total of 4,687 participants were included. …”
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A human-on-the-loop approach for labelling seismic recordings from landslide site via a multi-class deep-learning based classification model by Jiaxin Jiang, David Murray, Vladimir Stankovic, Lina Stankovic, Clement Hibert, Stella Pytharouli, Jean-Philippe Malet

“…To ensure reproducibility, a catalogue of training events is provided as supplementary material. …”
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Task-Driven Real-World Super-Resolution of Document Scans by Maciej Zyrek, Tomasz Tarasiewicz, Jakub Sadel, Aleksandra Krzywon, Michal Kawulok

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Operational evaluation of the deployment of Malaria/CRP Duo and Dengue Duo rapid diagnostic tests for the management of febrile illness by village malaria workers in rural Cambodia by Marc T. Visser, Dysoley Lek, Bipin Adhikari, Arjun Chandna, Moul Vanna, Sam Ol, Voeurng Bunreth, Chan Davoeung, Yok Sovann, Dafne Umans, Yoel Lubell, Rusheng Chew, Richard J. Maude, Rob W. van der Pluijm, Rupam Tripura, Naomi Waithira, Siv Sovannaroth, Michèle van Vugt, Lorenz von Seidlein, Mavuto Mukaka, Arjen Dondorp, Thomas J. Peto, James J. Callery

“…VMWs in 78 villages in Battambang and Pailin Provinces were trained and provided with either a Malaria/CRP Duo or Dengue Duo RDT to assess febrile patients. …”
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A spherical fuzzy WASPAS approach to prioritize the factors enhancing the effectiveness of physical education classroom teaching by Yuhan Gao, Ali Yu

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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

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RANFIS-Based Sensor System with Low-Cost Multi-Sensors for Reliable Measurement of VOCs by Keunyoung Kim, Woosung Yang

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Rice Leaf Nutrient Deficiency Classification System Using CAR-Capsule Network by M. Amudha, K. Brindha

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A Multi-Task Based Clustering Personalized Federated Learning Method by Ao Xiong, Han Zhou, Yu Song, Dong Wang, Xu Wei, Da Li, Bo Gao

“…Simulation experiments conducted on carbon emission prediction data demonstrate that the proposed algorithm performs better in various evaluation metrics compared with the Federated Averaging (FedAvg) algorithm and traditional clustering personalized federated learning algorithm. …”
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Compressive strength prediction of fly ash/slag-based geopolymer concrete using EBA-optimised chemistry-informed interpretable deep learning model by Yang Yu, Iman Munadhil Abbas Al-Damad, Stephen Foster, Ali Akbar Nezhad, Ailar Hajimohammadi

“…To optimise model accuracy, the enhanced bat algorithm (EBA) is designed for metaparameter tuning. …”
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