Model-Oriented Training of Coordinators of the Decentralized Control System of Technological Facilities With Resource Interaction by Volodymyr M. Dubovoi, Maria S. Yukhimchuk, Viacheslav V. Kovtun, Krzysztof R. Grochla

“…For the implementation of coordination methods, learning systems have an advantage since they can flexibly adapt to the specifics of each facility control. …”
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Effects of the Intervention Programme for a Mexican Adolescent with Absence Epilepsy and Learning Difficulties, Based on the Syndromic Analysis Methodology by Hansel Soto Hernández, Yulia Solovieva, Ernesto V. Ramírez Arroyo, Izabel Hazin

“…The case study refers to a Mexican 13-year-old male student, left-handed. Methods. The type of study was a single case study based on the theoretical-methodological assumptions of historical-cultural neuropsychology. …”
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Feature Selection Using Pearson Correlation for Ultra-Wideband Ranging Classification by Gita Indah Hapsari, Rendy Munadi, Bayu Erfianto, Indrarini Dyah Irawati

“…These findings highlight the effectiveness of Pearson correlation-based feature selection in improving UWB-based indoor positioning systems. …”
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A Machine Learning Model Based on MRI Radiomics to Predict Response to Chemoradiation Among Patients with Rectal Cancer by Filippo Crimì, Carlo D’Alessandro, Chiara Zanon, Francesco Celotto, Christian Salvatore, Matteo Interlenghi, Isabella Castiglioni, Emilio Quaia, Salvatore Pucciarelli, Gaya Spolverato

“…Background: With rectum-sparing protocols becoming more common for rectal cancer treatment, this study aimed to predict the pathological complete response (pCR) to preoperative chemoradiotherapy (pCRT) in rectal cancer patients using pre-treatment MRI and a radiomics-based machine learning approach. Methods: We divided MRI-data from 102 patients into a training cohort (<i>n</i> = 72) and a validation cohort (<i>n</i> = 30). …”
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Research on Detection Methods for Dynamic Ship Targets in Complex Marine Environment From Visible Light Images by Yao Wang, Yi Jiang, Weigui Zeng, Silei Cao

“…Based on this, the article proposes an integrated method combining dynamic target detection algorithms, edge detection operators, and deep learning‐based target detection algorithms. …”
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Problem Solving Approach Based on Blended Learning on Trigonometric Comparison of Right Triangles on Mathematical Concept Understanding Ability by Yosafat Ardian Kristiarta, Wahyu Setyaningrum, Marsigit

“…Statistical tests and classroom observations show positive results, indicating that this approach is the right choice to help students learn mathematics. …”
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Deep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma. by Linshan Zhou, Mu Yang, Jiadi Luo, Hongjing Zang, Songqing Fan, Yuting Zhan

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Refining the Feasibility of Machine‐Learning‐Based Diagnostic Model Utilizing Gut Microbiota Analysis for Colorectal Cancer Screening by Shintaro Okumura, Yusuke Konishi, Taku Kitano, Tomonori Matsumoto, Kazutaka Obama, Satoshi Nagayama, Eiji Hara

“…ABSTRACT Background Recently, we developed a colorectal cancer (CRC) diagnostic model based on a machine learning algorithm with gut microbiota analysis. …”
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Deep Learning-Based Navigation System for Automatic Landing Approach of Fixed-Wing UAVs in GNSS-Denied Environments by Ying-Xi Lin, Ying-Chih Lai

“…In this study, a deep learning-based navigation system for the automatic landing of fixed-wing UAVs in GNSS-denied environments is proposed to serve as an alternative navigation system. …”
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Machine learning-driven insights into self-healing silicon-based anodes for high-performance lithium-ion batteries by Mahta Moazzenzadeh, Mahmoud Samadpour

“…SHAP analysis revealed that ether functional groups, donor and acceptor hydrogen bonds, and dual-interconnected rings have the most positive impact on preserving battery capacity. In this study, we introduce a set of design principles for selecting functional groups aimed at enhancing the self-healing capabilities and prolonging the lifespan of Si-based LIBs. …”
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App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning. by Leila F Dantas, Igor T Peres, Leonardo S L Bastos, Janaina F Marchesi, Guilherme F G de Souza, João Gabriel M Gelli, Fernanda A Baião, Paula Maçaira, Silvio Hamacher, Fernando A Bozza

“…Hence, we aim to use the combination of symptoms to build a predictive model as a screening tool to identify people and areas with a higher risk of SARS-CoV-2 infection to be prioritized for testing.<h4>Materials and methods</h4>We performed a retrospective analysis of individuals registered in "Dados do Bem," a Brazilian app-based symptom tracker. …”
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Community-Based Tobacco Smoking Cessation Programmes Among Adolescents in Sarawak: Lesson Learned from Process Evaluation by Siddiq Muhammad, Md Mizanur Rahman, Sabrina Binti Lukas, Kamarudin Bin Kana, Merikan Bin Aren, Rudy Ngau Ajeng, Mohd Faiz Gahamat

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Advancing deep learning-based segmentation for multiple lung cancer lesions in real-world multicenter CT scans by Xavier Rafael-Palou, Ana Jimenez-Pastor, Luis Martí-Bonmatí, Carlos F. Muñoz-Nuñez, Mario Laudazi, Ángel Alberich-Bayarri

“…Relevance statement AI-driven segmentation comprehensively captures lesion burden, enhancing lung cancer assessment and disease monitoring Key Points Automatic multi-instance lung cancer lesion segmentation is underexplored yet crucial for disease assessment. Developed a deep learning-based segmentation pipeline trained on multi-center real-world data, which reached 85% sensitivity at external validation. …”
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MRI-based machine learning radiomics for prediction of HER2 expression status in breast invasive ductal carcinoma by Hong-Jian Luo, Jia-Liang Ren, Li mei Guo, Jin liang Niu, Xiao-Li Song

“…Objective: This study aimed to explore the effectiveness of a multisequence magnetic resonance imaging (MRI)-based machine learning radiomics model in classifying the expression status of HER2, including HER2-positive, HER2-low, and HER2 completely negative (HER2-zero), among patients with IDC. …”
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Recognition of field-grown tobacco plant type characteristics based on three-dimensional point cloud and ensemble learning by JIA Aobo, DONG Tianhao, ZHANG Yan, ZHU Binglin, SUN Yanguo, WU Yuanhua, SHI Yi, MA Yuntao, GUO Yan

“…To develop an efficient method for quantifying tobacco plant types in the field, the three-dimensional (3D) point clouds of individual plant of five tobacco cultivars were reconstructed based on multi-view image sequences using the structure from motion method. …”
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Federated learning-based hybrid convolutional recurrent neural network for multi-class intrusion detection in IoT networks by Prabu Selvam, P. Karthikeyan, S. Manochitra, A. V. L. N. Sujith, T. Ganesan, Rajaram Ayyasamy, Mohammed Shuaib, Shadab Alam, A. Rajendran

“…For multi-class intrusion detection in IoT networks, this study proposed an novel hybrid convolutional recurrent neural network (CRNN) model based on federated learning. By integrating federated learning, the proposed approach ensures privacy by enabling decentralized model training among IoT devices without exchanging sensitive data. …”
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Pilot Trial of Quarterly Text-Based Patient Contacts to Increase Engagement in HIV Care Postpartum: Lessons Learned by Emily Johnson, Jillian Harvey, Katie Kirchoff, Rebecca Verdin, Samantha D’Orio, Kathryn King, Gweneth B. Lazenby

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Development of a Game-Based Learning: Airfield Lighting System Simulator Using Virtual Reality and Augmented Reality by Direstu Amalia, Viktor Suryan, Virma Septiani, Yeti Komalasari, Rio Rizko, Adha Febriansyah, Siti Salbiah Ristumanda, Muhammad Kristiawan, Oke Hendra

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A Web-Based Interface That Leverages Machine Learning to Assess an Individual&#x2019;s Vulnerability to Brain Stroke by Divyansh Bhandari, Arnav Agarwal, R. Reena Roy, Rajaram Priyatharshini, Rodriguez Rivero Cristian

“…Early identification of individuals at high risk of stroke can significantly improve preventive care outcomes. We present a web-based stroke risk assessment tool that uniquely combines an accessible user interface with robust machine learning modeling. …”
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Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology. by Yu Cai, Xi-Ru Huang, Sheng-Jia Wang, Ying-Chao Liang, De-Liang Liu, Shu-Fang Chu, Hui-Lin Li

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