Comparison of self-collected and healthcare worker-collected rectovaginal swabs for group B streptococcus detection in pregnancy using PCR with a commercial collection-enrichment d... by Iva Kukovica, Neža Omahen, Nika Klobučar, Martina Bučar, Anita Franko Rutar, Tina Perme, Tina Perme, Miha Lučovnik, Miha Lučovnik, Samo Jeverica, Samo Jeverica

“…Performance characteristics were calculated and compared between different diagnostics test algorithms using McNemar’s test for paired samples.ResultsOverall, GBS was detected in 18% (95% CI 13–23%; n = 40) of swabs A and 19% (95% CI 14–25%; n = 43) of swabs B. …”
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Comparative analysis of the frequency of comorbid diseases in axial psoriatic arthritis and other variants of axial spondyloarthritis. Data from a hospital cohort by A. A. Yanushonite, Yu. L. Korsakova, T. V. Korotaeva, E. E. Gubar, E. Yu. Loginova, M. M. Urumova, A. E. Dimitreva, S. I. Glukhova

“…A high frequency of comorbidities, mainly cardiovascular and metabolic diseases, was found in both groups. These data should be considered in the choice of therapy and optimization of existing treatment algorithms.…”
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An Explainable Machine Learning Approach for IoT-Supported Shaft Power Estimation and Performance Analysis for Marine Vessels by Yiannis Kiouvrekis, Katerina Gkirtzou, Sotiris Zikas, Dimitris Kalatzis, Theodor Panagiotakopoulos, Zoran Lajic, Dimitris Papathanasiou, Ioannis Filippopoulos

“…A diverse set of models—ranging from traditional algorithms such as Decision Trees and Support Vector Machines to advanced ensemble methods like XGBoost and LightGBM—were developed and evaluated. …”
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Screening and Risk Analysis of Atrial Fibrillation After Radiotherapy for Breast Cancer: Protocol for the Cross-Sectional Cohort Study “Watch Your Heart (WATCH)” by Laura Saint-Lary, Baptiste Pinel, Loic Panh, Gaelle Jimenez, Julien Geffrelot, Youlia Kirova, Jeremy Camilleri, David Broggio, Marie-Odile Bernier, Corinne Mandin, Christelle Levy, Serge Boveda, Juliette Thariat, Sophie Jacob

“…AF can increase the risk of stroke and other serious cardiovascular complications, compromising patients’ quality of life and survival. Screening of AF, both asymptomatic and symptomatic forms, is therefore essential for optimal management. …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…A combined model was further constructed by integrating both feature sets, and model performance was compared to identify the optimal predictive model.Results‍　‍This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model. …”
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A Review and Tutorial on Machine Learning-Enabled Radar-Based Biomedical Monitoring by Daniel Krauss, Lukas Engel, Tabea Ott, Johanna Braunig, Robert Richer, Markus Gambietz, Nils Albrecht, Eva M. Hille, Ingrid Ullmann, Matthias Braun, Peter Dabrock, Alexander Kolpin, Anne D. Koelewijn, Bjoern M. Eskofier, Martin Vossiek

“…Machine learning (ML) algorithms can be trained to extract meaningful information from radar data for medical experts, enhancing not only diagnostic capabilities but also contributing to advancements in disease prevention and treatment. …”
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Examining the Role of Social Media in New Social Movements A Case Study of the Black Lives Matter Movement by Ali Davari, Mostafa Ghaffari

“…Additionally, the movement’s reliance on private platforms such as Twitter and Facebook raises concerns about censorship, algorithmic bias, and data privacy—issues not addressed in Melucci’s original framework.Conclusion: By integrating Melucci’s theoretical insights with the lived realities of the Black Lives Matter movement, this study demonstrates how social media can both strengthen and complicate the dynamics of new social movements. …”
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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

“…An averaging voting ensemble model is developed by integrating the two highest-performing algorithms, LRNN and TRF, leveraging the strengths of both algorithms. …”
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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

“…MethodsThis study used decision tree algorithms—ID3 and CART—on a data set of 60 hepatitis B surface antigen (HBsAg)–positive pregnant women. …”
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Noninvasive prediction of meningioma brain invasion via multiparametric MRI⁃based brain⁃tumor interface radiomics by CHENG Xing, WANG Zhi⁃chao, LI Hua⁃ning, WANG Xie⁃feng, YOU Yong⁃ping

“…DCA showed that this model demonstrated the best clinical utility with the highest net benefit area in both the training set (0.087) and the testing set (0.094). …”
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Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis by Xudong Shen, Xudong Shen, Xudong Shen, Guoxiang Li, Guoxiang Li, Guoxiang Li, Junfeng Yao, Junfeng Yao, Junfeng Yao, Junping Yang, Xiaobo Ding, Xiaobo Ding, Xiaobo Ding, Zongyao Hao, Zongyao Hao, Zongyao Hao, Yan Chen, Yang Chen, Yang Chen, Yang Chen

“…Differentially expressed genes (DEGs) were subsequently analyzed using 10 commonly used machine learning algorithms, generating 101 unique combinations to identify the final DEGs. …”
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Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition by Rafael T. Sousa, Gustavo D. M. Silva, Paula L. L. Pinto, Juliano Backes, Amanda S. Mota, Thiago M. Paixao, Maria G. S. Teixeira, Wilian H. Hisatugu, Anilton S. Garcia, Kelly S. Prado, Rodrigo S. Dias, Marco A. Galletta, Hermano Tavares

“…Depression and anxiety during pregnancy are critical public health concerns, impacting both maternal and fetal well-being. The onset of these mental health conditions during pregnancy can lead to adverse outcomes, such as preterm birth and impaired infant development. …”
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Detection of Coffee Leaf Miner Using RGB Aerial Imagery and Machine Learning by Emerson Ferreira Vilela, Cileimar Aparecida da Silva, Jéssica Mayara Coffler Botti, Elem Fialho Martins, Charles Cardoso Santana, Diego Bedin Marin, Agnaldo Roberto de Jesus Freitas, Carolina Jaramillo-Giraldo, Iza Paula de Carvalho Lopes, Lucas de Paula Corrêdo, Daniel Marçal de Queiroz, Giuseppe Rossi, Gianluca Bambi, Leonardo Conti, Madelaine Venzon

“…A set of four machine learning algorithms was utilized: Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD). …”
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Comparison of dose calculation approaches and clinical dose–response in image-guided head&neck brachytherapy of the oral cavity by Sabrina Schaller, Vratislav Strnad, Claudia Schweizer, Dorota Lubgan, Ricarda Merten, Rainer Fietkau, Christoph Bert, Andre Karius

“…Purpose: Model-based dose calculation algorithms (MBDCAs) are increasingly applied in brachytherapy, but their considerations in dose–response analyses is still lacking. …”
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The pre- and post-COVID-19 pandemic dengue fever patterns in southeastern coastal China in 2019 and 2024: molecular evolution and strain replacement by Tianran Zhang, Yaqi Shi, Leyi Zhang, Jian Wang, Chengchao Yu, Binbin Lv, Sisi Wu, Yiru Huang, Xuewei Liu, Hupiao Dai, Mingshi Zhou, Yanjuan Liao, Wei Wang, Guankai Lin

“…Recombination was analyzed using seven detection algorithms implemented in RDP4. Hamming distances were used to profile amino acid substitutions. …”
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Dynamic forecasting module for chronic graft-versus-host disease progression based on a disease-associated subpopulation of B cells: a multicenter prospective studyResearch in cont... by Yuanchen Ma, Jieying Chen, Zhiping Fan, Jiahao Shi, Gang Li, Xiaobo Li, Tao Wang, Na Xu, Jialing Liu, Zhishan Li, Heshe Li, Xiaoran Zhang, Dongjun Lin, Wu Song, Qifa Liu, Weijun Huang, Xiaoyong Chen, Andy Peng Xiang

“…To validate cGPS, we conducted both retrospective and prospective multi-center studies involving 91 patients (25 non-GVHD and 66 cGVHD cases). …”
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Advancing sustainability: The impact of emerging technologies in agriculture by Ashoka Gamage, Ruchira Gangahagedara, Shyamantha Subasinghe, Jeewan Gamage, Chamini Guruge, Sera Senaratne, Thevin Randika, Chamila Rathnayake, Zammil Hameed, Terrence Madhujith, Othmane Merah

“…The integration of data analytics and machine learning algorithms is transforming supply chain management and enhancing the capabilities of predictive analytics in the context of crop diseases. …”
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Prognostic value of multi-PLD ASL radiomics in acute ischemic stroke by Zhenyu Wang, Yuan Shen, Xianxian Zhang, Qingqing Li, Congsong Dong, Shu Wang, Haihua Sun, Mingzhu Chen, Xiaolu Xu, Pinglei Pan, Pinglei Pan, Zhenyu Dai, Fei Chen, Fei Chen

“…Statistical analysis using the DeLong test revealed its significant outperformance compared to both the clinical model (AUC = 0.658, p < 0.001) and the CBF radiomics model (AUC = 0.755, p = 0.002). …”
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A novel multiscale feature enhancement network using learnable density map for red clustered pepper yield estimation by Chenming Cheng, Chenming Cheng, Jin Lei, Jin Lei, Zicui Zhu, Lijian Lu, Lijian Lu, Zhi Wang, Zhi Wang, Jiali Tao, Jiali Tao, Xinyan Qin, Xinyan Qin

“…The proposed method provides an robust algorithmic support for efficient and intelligent yield estimation in RCP.…”
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Shared diagnostic genes and potential mechanism between PCOS and recurrent implantation failure revealed by integrated transcriptomic analysis and machine learning by Wenhui Chen, Wenhui Chen, Wenhui Chen, Qingling Yang, Qingling Yang, Qingling Yang, Linli Hu, Linli Hu, Linli Hu, Mengchen Wang, Mengchen Wang, Mengchen Wang, Ziyao Yang, Ziyao Yang, Ziyao Yang, Xinxin Zeng, Xinxin Zeng, Xinxin Zeng, Yingpu Sun, Yingpu Sun, Yingpu Sun

“…Through the functional enrichment of twelve shared genes and two diagnostic genes, we found that both PCOS and RIF patients had disturbances in metabolites related to the TCA cycle, which eventually led to the massive activation of immune cells.…”
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