Chronic stress in practice assistants: An analytic approach comparing four machine learning classifiers with a standard logistic regression model. by Arezoo Bozorgmehr, Anika Thielmann, Birgitta Weltermann

“…The performance of these models was compared in terms of predictive accuracy based on the 'operating area under the curve' (AUC), sensitivity, and positive predictive value.…”
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A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective by Dung Nguyen Tien, Huong Thi Thu Bui, Tram Hoang Thi Ngoc, Thuy Thi Pham, Dac Trung Nguyen, Huyen Nguyen Thi Thu, Thi Thu Hang Vu, Thi Lan Anh Luong, Lan Thu Hoang, Ho Cam Tu, Nina Körber, Tanja Bauer, Lam Khanh Ho

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Prior-FOVNet: A Multimodal Deep Learning Framework for Megavoltage Computed Tomography Truncation Artifact Correction and Field-of-View Extension by Long Tang, Mengxun Zheng, Peiwen Liang, Zifeng Li, Yongqi Zhu, Hua Zhang

“…Specifically, to address the intensity discrepancies between different imaging modalities, we employ a contrastive learning-based GAN, named TransNet, to transform KVCT images into synthesized MVCT (sMVCT) images. …”
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Machine learning for predicting neoadjuvant chemotherapy effectiveness using ultrasound radiomics features and routine clinical data of patients with breast cancer by Pu Zhou, Pu Zhou, Hongyan Qian, Pengfei Zhu, Jiangyuan Ben, Jiangyuan Ben, Guifang Chen, Qiuyi Chen, Lingli Chen, Jia Chen, Ying He, Ying He

“…BackgroundThis study explores the clinical value of a machine learning (ML) model based on ultrasound radiomics features of primary foci, combined with clinicopathologic factors to predict the pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) for patients with breast cancer (BC).MethodWe retrospectively analyzed ultrasound images and clinical information from 231 participants with BC who received NAC. …”
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Clinical-radiomics hybrid modeling outperforms conventional models: machine learning enhances stratification of adverse prognostic features in prostate cancer by Minghan Jiang, Minghan Jiang, Zeyang Miao, Run Xu, Mengyao Guo, Xuefeng Li, Guanwu Li, Peng Luo, Su Hu, Su Hu

“…ObjectiveThis study aimed to develop MRI-based radiomics machine learning models for predicting adverse pathological prognostic features in prostate cancer and to explore the feasibility of integrating radiomics with clinical characteristics to improve preoperative risk stratification, addressing the limitations of conventional clinical models.MethodsA retrospective cohort of 137 prostate cancer patients between January 2021 and April 2023 with preoperative MRI and postoperative pathology data was divided into adverse-feature-positive (n=85) and negative (n=52) groups. …”
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Exploring the mediating role of social support and learning engagement in the relationship between physical activity and academic achievement in secondary school students by Jun Xiang, Kelei Guo, Jia Gao, Yun Gao, ShiLei Liu

“…Therefore, the purpose of this study was to investigate the relationship between physical activity and academic achievement of secondary school students, and to verify the mediating role of social support and learning engagement between them.MethodsBased on the purpose, a survey was conducted involving 3,230 secondary school students (M age = 13.21, SD age = 0.54) in Guangdong Province, utilizing the Physical Activity Level Scale, Academic Achievement Scale, Perceived Social Support Scale, and Learning Engagement Scale. …”
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Screening and Management of Obstructive Sleep Apnea and Daytime Sleepiness Among Professional Drivers in Tunisia: Protocol for a Machine Learning Study by Sameh Msaad, Nesrine Kammoun, Rahma Gargouri, Rim Khemakhem, Amira Triki, Narjes Abid, Sonia Fehri, Kaouthar Kallel, Rim Kammoun, Leila Douik EL Gharbi, Sonia MaalejBellaj, Heni Bouhamed, Ahmed Abdelghani, Chiraz Aichaouia, Mohamed Turki, Samy Kammoun

“…We will also evaluate the risk of accidents associated with OSA and EDS before and after the treatment. MethodsThis will be a population-based and prospective study of about 3000 professional drivers. …”
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Optimizing UAV Location for Deployment in Cell-Free Massive MIMO Networks Using a Soft Actor-Critic Reinforcement Learning by Okello Kenneth, Elijah Mwangi, Dominic Bernard Onyango Konditi

“…In addressing these issues, we propose a deployment technique using Soft Actor-Critic (SAC), a deep reinforcement learning method, to autonomously determine the optimal placement of the UAV within a given pre-defined coverage area, thereby maximizing channel capacity and throughput. …”
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Lymph Node Involvement Prediction Using Machine Learning: Analysis of Prostatic Nodule, Prostatic Gland, and Periprostatic Adipose Tissue (PPAT) by Eliodoro Faiella, Giulia D’amone, Raffaele Ragone, Matteo Pileri, Elva Vergantino, Bruno Beomonte Zobel, Rosario Francesco Grasso, Domiziana Santucci

“…This study included patients who underwent prostatectomy and lymphadenectomy with complete histological examination and previous staging mp-MRI and were divided into two groups based on lymph node status (positive/negative). Data were collected from each patient, including clinical information, radiomics, and semantic data (such as tumor MRI characteristics, histological tumor details, and lymph node status (LNS)). …”
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Crossroad control algorithm based on V2I-interaction by A. N. Klimovich, V. N. Shuts

“…Constantly increasing number of vehicles and traffic volume requires improvement of methods and algorithms of traffic control. Such improvement becomes possible due to the spreading of global navigation and positioning systems, the development of wireless communication technologies and mobile internet, the advance in specialized technologies for interaction between vehicles and road infrastructure (V2I), the enhancement of machine learning models, computer vision algorithms, the emergence of driverless cars. …”
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Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men by Lin Wang, Jing Xie, Zhaoyan Gu, Xinyu Miao, Lichao Ma, Shuangtong Yan, Yanping Gong, Chunlin Li, Banruo Sun, Yue Ruan

“…Individuals with FPG levels higher than 5.1 mmol/L were more likely to have I-IGT; the performance metrics for this cut-off value were: 89.35% accuracy, 89.79% recall, 85.22% F1 score, 81.09% PPV, 94.38% NPV, and 0.95 AUC.ConclusionMachine learning models based on demographic and clinical characteristics offer a cost-effective method for predicting I-IGT in Chinese Han men aged over 50, without the need for an OGTT. …”
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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

“…Traditional single models show limitations in processing large-scale multimodal data.MethodsThis study constructed an interpretable ensemble learning model for maize seed variety identification through improved differential evolutionary algorithm and multimodal data fusion. …”
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Analysis of Effective Classroom Management Strategies to Create a Conducive Learning Environment for Elementary School Students through Document Studies by Bambang Afriadi, Fitri Fitri

“…The implications of this study underscore the importance of teacher professional development in adopting adaptive and evidence-based classroom management strategies to enhance the quality of learning at the primary education level.…”
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Indoor fire and smoke detection based on optimized YOLOv5. by Md Shafak Shahriar Sozol, M Rubaiyat Hossain Mondal, Achmad Husni Thamrin

“…Ensuring safety and safeguarding indoor properties require reliable fire detection methods. Traditional detection techniques that use smoke, heat, or fire sensors often fail due to false positives and slow response time. …”
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Stock market trend prediction using deep neural network via chart analysis: a practical method or a myth? by Erfan Radfar

“…We explore the dynamics of the stock market and prominent classical methods and deep learning-based approaches that are used to forecast prices and market trends. …”
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Research on intrusion detection model based on synchronization of heterogenous executer by YU Hong, ZHU Zhengbin, WEI Shuai, GUO Wei, LAN Julong

“…Intrusion detection and cybersecurity situational awareness technologies based on machine learning and deep learning have generally been limited by their reliance on prior knowledge and pre-training, which restricts their accuracy in detecting various types of attacks. …”
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Computer-Aided Monitoring of Fetus Health From Ultrasound Images: A Review by Deniz Ataş, Yonca Bayrakdar Yılmaz

“…This study first introduces the indicators for identifying anomalies in fetus and gives basic information about computer-based methods such as traditional image processing, machine learning and deep learning. …”
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Major aspects of STEM education based on U.S. government initiatives by Liliya Batyuk

“…Theoretical-generalizing method and interpretation method (for formulating and substantiating conclusions based on the results of the study) were also used. …”
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Development of STEM-based worksheets to improve student literacy skills by Cahaya Febriyanti Simanjuntak, H. Hasruddin, Daulat Saragi

“…This indicates that the STEM-based worksheets positively impact students' literacy abilities.   …”
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SAR Small Ship Detection Based on Enhanced YOLO Network by Tianyue Guan, Sheng Chang, Chunle Wang, Xiaoxue Jia

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