AI and Data Analytics in the Dairy Farms: A Scoping Review by Osvaldo Palma, Lluis M. Plà-Aragonés, Alejandro Mac Cawley, Víctor M. Albornoz

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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…This study aimed to develop an interpretable machine learning (ML) model using routine laboratory parameters to predict blood culture positivity. …”
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Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results by Andy Victor Pakpahan, Fahmi Reza Ferdiansyah, Robby Gustian, Muhammad Nur Faiz, Sukma Aji

“…Sentiment analysis is a text processing technique aimed at identifying opinions and emotions within a sentence. Machine learning is commonly applied in this area, with algorithms such as Naïve Bayes, Support Vector Machine (SVM), and Random Forest being frequently used. …”
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Machine learning-based identification of key biotic and abiotic drivers of mineral weathering rate in a complex enhanced weathering experiment [version 2; peer review: 1 approved,... by Thomas Corbett, Harun Niron, Lukas Rieder, Reinaldy P. Poetra, Abhijeet Singh, Michiel Van Tendeloo, Siegfried E. Vlaminck, Steven Latré, Jan Willem van Groenigen, Jens Hartmann, Alix Vidal, Anna Neubeck, Mathilde Hagens, Ivan A. Janssens, Tim Verdonck, Sara Vicca, Thomas Servotte, Iris Janssens, Steven Mortier, Tullia Calogiuri

“…The resulting changes in dissolved, solid, and total inorganic carbon (∆TIC), and total alkalinity were calculated as indicators of carbon dioxide removal through mineral weathering. Three machine learning models, Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest and eXtreme Gradient Boosting (XGB) regression, were used to predict these indicators. …”
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Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based... by Yasin P, Ding L, Mamat M, Guo W, Song X

“…The optimal model was further refined through threshold tuning to enhance performance metrics. …”
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Ensemble semi-supervised learning in facial expression recognition by Purnawansyah Purnawansyah, Adam Adnan, Herdianti Darwis, Aji Prasetya Wibawa, Triyanna Widyaningtyas, Haviluddin Haviluddin

“…For future research, it is recommended to employ cross-validation methods for more robust performance evaluation, explore additional data augmentation techniques, optimize ensemble configurations, and address the computational efficiency of the model to better advance FER technologies.…”
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Predicting Insemination Outcome in Holstein Dairy Cattle using Deep Learning by Mohammad Alishahi, Mahdi Ravakhah

“…Introduction: Development of a predictive model using machine learning can help livestock farmers to increase their understanding of the performance potential of their livestock. …”
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Innovative data augmentation strategy for deep learning on biological datasets with limited gene representations focused on chloroplast genomes by Mohammad Ali Abbasi-Vineh, Shirin Rouzbahani, Kaveh Kavousi, Masoumeh Emadpour

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Dual-radiomics based on SHapley additive explanations for predicting hematologic toxicity in concurrent chemoradiotherapy patients by Luqiao Chen, Zhipeng He, Qianxi Ni, Qionghui Zhou, Xizi Long, Wenbin Yan, Qian Sui, Jiheng Liu

“…Abstract Background This study investigates the application of a machine learning model that integrates radiomic features and dosiomic features to predict hematologic toxicity (HT) in patients with advanced cervical cancer undergoing concurrent chemoradiotherapy (CCRT). …”
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Stochastic estimation of soil hydraulic conductivity utilizing self-organizing map method by Kyeongmo Koo, Hyunki Kim

“…Using the extensive FLSOIL database of 6,487 soil samples from Florida, the SOM-based ksat estimation model is optimized based on map size and feature selection, then compared with seven empirical equations and three supervised machine learning models. …”
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Anchor Dragging Risk Estimation Strategy from Supervised Cost-Sensitive Learning by Sang-Lok Yoo, Shem Otoi Onyango, Joo-Sung Kim, Kwang-Il Kim

“…This study analyzed a large dataset of ships in anchorage areas to develop a machine learning (ML) model that estimates the risk of anchor dragging using a binary classification system that differentiates between dragging and non-dragging incidents. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…Key variables for predictive modeling were identified through LASSO (least absolute shrinkage and selection operator) regression, SVM–RFE (support vector machine–recursive feature elimination), and random forest techniques. …”
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Artificial intelligence techniques by Ahmad Gholizadeh, Ali Shabani

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Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation by Muhammad Yasir, Mubashir Gulzar, Muhammad Saad Khan, Alexis Mounge Nanimina, Imtiaz Ali, Shahid Iqbal

“…These results highlight the potential of ML models in enhancing machining efficiency and sustainability in drilling.…”
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Complete Coverage Path Planning for Wind Turbine Blade Wall-Climbing Robots Based on Bio-Inspired Neural Networks and Energy Consumption Model by Da Chen, Gang Yu, Shuchen Huang

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TPE-LCE-SHAP: A Hybrid Framework for Assessing Vehicle-Related PM2.5 Concentrations by Hamad Almujibah, Abdulrazak H. Almaliki, Caroline Mongina Matara, Adil Abdallah Mohammed Elhassan, Khalaf Alla Adam Mohamed, Mudthir Bakri, Afaq Khattak

“…The framework integrates the Local Cascade Ensemble (LCE) model, optimized using the Tree-structured Parzen Estimator (TPE) strategy, with SHapley Additive exPlanations (SHAP) to enhance interpretability. …”
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Automated pain detection using facial expression in adult patients with a customized spatial temporal attention long short-term memory (STA-LSTM) network by Chin Wen Tan, Tiehua Du, Jing Chun Teo, Diana Xin Hui Chan, Wai Ming Kong, Ban Leong Sng

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Preliminary analysis of acoustic detection of the Red-throated Caracara in northern Costa Rica by Roberto Vargas-Masís, Diego Quesada

“…Advances in automatic acoustic detection have transformed bird ecology, allowing researchers to analyze bird populations using pattern matching algorithms, machine learning, and random forest models. Although these studies are limited in the country, it represents an area with great interdisciplinary potential for technological advances. …”
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A model for Managing the Competitive Activitiesof Top-Level Teams Based on Computer Vision Online by Sergei L. Goldstein, Andrey A. Polozov, Natalia V. Papulovskaya, Natalya A. Maltseva, Maxim V. Kraev

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Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning, Yue Sun

“…Accurate crop yield prediction is crucial for formulating agricultural policies, guiding agricultural management, and optimizing resource allocation. This study proposes a method for predicting yields in China’s major winter wheat-producing regions using MOD13A1 data and a deep learning model which incorporates an Improved Gray Wolf Optimization (IGWO) algorithm. …”
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