Research on intelligent detection method of new energy vehicle power battery based on improved ViBe algorithm by Lei Gu

“…Method: The method includes analyzing global light changes before foreground detection and updating the background model using the three-frame difference method. The system integrates hardware and software to process data with the ViBe algorithm, measuring voltage from twelve 18650-type lithium batteries. …”
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Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms by Chunxia Huang, Qiong Ma, Xiao Zeng, Jiawei He, Fengming You, Xi Fu, Yifeng Ren

“…Furthermore, the Bayesian optimization algorithm was used to optimize this best-performing model. …”
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Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic... by Peng Lyu, Na Xie, Xu-peng Shao, Shuai Xing, Xiao-yue Wang, Li-yun Duan, Xue Zhao, Jia-min Lu, Rong-fei Liu, Duo Zhang, Wei Lu, Kai-liang Fan

“…CD177, MCEMP1, MMP8, and OLAH were examined as diagnostic indicators for pediatric septic shock, revealing statistically significant differences (P < 0.01) and diagnostic efficacy in the validation cohort. …”
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Use of X means and C4.5 algorithms on lateral cephalometric measurements to identify craniofacial patterns by Merve Gonca, Mehmet Birol Özel

“…One-way ANOVA and Kruskal-Wallis tests were used to assess differences among clusters. Results A total of four clusters were obtained using the X-means algorithm. …”
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Assessment of Bone Aging—A Comparison of Different Methods for Evaluating Bone Tissue by Paweł Kamiński, Aleksander Gali, Rafał Obuchowicz, Michał Strzelecki, Adam Piórkowski, Marcin Kociołek, Elżbieta Pociask, Joanna Kwiecień, Karolina Nurzyńska

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Significance of EEG-electrode combinations while calculating filters with common spatial patterns by Wetzel, Dominik, Jacobs, Paul-Philipp, Winkler, Dirk, Grunert, Ronny

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Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder by Lei Tang, Liling Wu, Mengqin Dai, Nian Liu, Lu liu

“…We first applied gene set variation analysis (GSVA) and seven different immune infiltration algorithms to the GSE98793 dataset to determine the differences in signaling pathways, metabolic pathways, and immune cell infiltration between MDD patients and healthy controls. …”
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Efficacy of two radiographic algorithms for detection of peri-implant bone defects on cone-beam computed tomography scans by Faezeh Yousefi, Ali Heidari, Azita Ehsani, Maryam Farhadian, Marzieh Ehsani

“…Results The inter-observer agreement was high for detection of all defects in all modes except with ANR. No significant difference was found in AUC and diagnostic accuracy of different scan modes (P > 0.05). …”
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A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging by Joy Chakra Bortty, Gouri Shankar Chakraborty, Inshad Rahman Noman, Salil Batra, Joy Das, Kanchon Kumar Bishnu, Md Tanvir Rahman Tarafder, Araf Islam

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“Real‐world” performance of the Confirm Rx™ SharpSense AF detection algorithm: UK Confirm Rx study by Andre Briosa e Gala, Michael T. B. Pope, Milena Leo, Alexander J. Sharp, Abhirup Banerjee, Duncan Field, Honey Thomas, Richard Balasubramaniam, Ross Hunter, Roy S. Gardner, David Wilson, Mark M. Gallagher, Julian Ormerod, John Paisey, Nick Curzen, Timothy R. Betts

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Super‐resolution reconstruction algorithm for medical images by fusion of wavelet transform and multi‐scale adaptive feature selection by QiaoSu Wang, Qiaomei Ma

“…Image super‐resolution methods can significantly enhance CT image quality, thereby improving diagnostic accuracy. To better extract detailed features and enhance the cascading effects of different feature levels, we propose a novel medical image super‐resolution algorithm that integrates discrete wavelet transform and multi‐scale adaptive feature selection. …”
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Proactive vs. passive algorithmic ethics practices in healthcare: the moderating role of healthcare engagement type in patients’ responses by Sheng Shu, Qinglin Luo, Zhiqing Chen

“…This study examined the effects of proactive versus passive algorithmic ethics practices on patient responses across different healthcare engagement types (privacy-focused vs. utility-focused). …”
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A Model for Detecting <i>Xanthomonas campestris</i> Using Machine Learning Techniques Enhanced by Optimization Algorithms by Daniel-David Leal-Lara, Julio Barón-Velandia, Lina-María Molina-Parra, Ana-Carolina Cabrera-Blandón

“…To address this issue, this study developed a model that combines fuzzy logic and neural networks, optimized with intelligent algorithms, to detect symptoms of this foliar disease in 15 essential crop species under different environmental conditions using images. …”
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Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation by Guowei Han, Tianliang Jin, Li Zhang, Chen Guo, Hua Gui, Risu Na, Xuesong Wang, Haihua Bai

“…This research was aimed at exploring the diagnostic and screening effect of composite echocardiography based on the artificial intelligence (AI) segmentation algorithm on fetal congenital heart disease (CHD) during pregnancy, so as to reduce the birth rate of newborns with CHD. …”
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A pulmonary hypertension targeted algorithm to improve referral to right heart catheterization: A machine learning approach by Paola Argiento, Anna D'Agostino, Rossana Castaldo, Monica Franzese, Matteo Mazzola, Ekkehard Grünig, Lavinia Saldamarco, Valeria Valente, Alessandra Schiavo, Erica Maffei, Davide Lepre, Antonio Cittadini, Eduardo Bossone, Michele D'Alto, Luna Gargani, Alberto Maria Marra

“…Aim of the current study was to develop a Machine Learning (ML) algorithm based on the analysis of anamnestic data to predict the presence of an invasively measured PH. …”
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Explicit Model for Chiller Fault Diagnosis Based on Multi-objective Regression with Different Weights by Wu Kongrui, Han Hua, Yang Yuting, Lu Hailong, Ling Minbin

“…Based on the cross-entropy loss function and stochastic gradient descent algorithm, a weight regression fault diagnosis model was established for seven common faults in a chiller. …”
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Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm by G. Ayappan, S. Anila

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RETRACTED ARTICLE: Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnosti... by Zhang Zhang, Fangfang Chen, Xiaoxiao Deng

“…Furthermore, using machine learning algorithms, we constructed a clinical prognostic model and validated and optimized it via extensive clinical data. …”
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Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning by Chao Lin, Yue Wan, Yong Xu, Qingsong Zou, Xiaoxiao Li

“…Machine learning (ML) algorithms identified feature genes of OA-macrophages. …”
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Development and Validation of an Algorithm for Segmentation of the Prostate and its Zones from Three-dimensional Transrectal Multiparametric Ultrasound Images by Daniel L. van den Kroonenberg, Florian T. Delberghe, Auke Jager, Arnoud W. Postema, Harrie P. Beerlage, Wim Zwart, Massimo Mischi, Jorg R. Oddens

“…Manual segmentation was performed using a custom tool, and an algorithm was developed using a convolutional neural network based on the U-Net architecture. …”
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