Arrhythmia detection with transfer learning architecture integrating the developed optimization algorithm and regularization method by Fatma Akalın, Pınar Dervişoğlu Çavdaroğlu, Mehmet Fatih Orhan

“…Training was performed under the same conditions as the training performed on 2-category datasets. …”
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The VOICE study - A before and after study of a dementia communication skills training course. by Rebecca O'Brien, Sarah E Goldberg, Alison Pilnick, Suzanne Beeke, Justine Schneider, Kate Sartain, Louise Thomson, Megan Murray, Bryn Baxendale, Rowan H Harwood

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Exploring immune-inflammation markers in psoriasis prediction using advanced machine learning algorithms by Li Yang, Shixin He, Li Tang, Xiao Qin, Yan Zheng

“…Subsequently, nine classification algorithms were developed using the processed training set, including random forest, neural networks, XGBoost, k-nearest neighbors, gradient boosting, logistic regression, naïve Bayes, AdaBoost, and SVMs. …”
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Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure by GUO Xiaojing, ZHAO Xiaoyuan, ZOU Songlin

“…Higher identification precision and efficiency serve as reference indices for evaluating the model. The improved RMCA algorithm applies four branches in the initial layers, which differs from the original re-parameterized structure. …”
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Estimation of soil free Iron content using spectral reflectance and machine learning algorithms by Wanzhu Ma, Hongkui Zhou, Hao Hu, Zhiqing Zhuo, Kangying Zhu, Guangzhi Zhang

“…Over-fitting may have occurred in our study when employing the CR transform and RF algorithm. Their models had high accuracy in training and low accuracy in testing. …”
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Grading Traditional Exams Using Image Processing Techniques and the Word Similarity Weights Algorithm by Yahya Gedik, Serdar Solak, Mustafa Hikmet Bilgehan Uçar

“…Educational institutions have started to support their computer-aided trainings with online and offline platforms. Exam evaluations can be carried out quickly by the system using these platforms. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…The YOLOv5 (you only look once) method is designed to rapidly and accurately detect specific target objects and their locations in images after training on a sampled dataset. The YOLOv5 algorithm adopted in this study excels at detecting small targets and provides multi-scale detection, strong versatility, fast training, inference speeds, and adaptable fine-tuning capabilities. …”
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Unmanned Aerial Vehicles (UAV) Networking Algorithms: Communication, Control, and AI-Based Approaches by Mien L. Trinh, Dung T. Nguyen, Long Q. Dinh, Mui D. Nguyen, De Rosal Ignatius Moses Setiadi, Minh T. Nguyen

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Screening of glioma susceptibility SNPs and construction of risk models based on machine learning algorithms by Mingjun Hu, Jie Hao, Jie Wei

“…Key SNPs associated with glioma susceptibility were identified through LASSO, SVM-RFE algorithm, and likelihood ratio. A nomogram was constructed to predict glioma risk, and its predictive accuracy was evaluated using calibration and ROC curves. …”
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Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms by Juchao Chen, Zicheng Lei, Zongcai Duan, Zhili Wen

“…Abstract This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction model for spontaneous rupture bleeding via a machine learning algorithm, and validate and evaluate the predictive efficacy of the model. …”
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Validation of a Novel Data-Driven Algorithm to Detect Atypical Prescriptions in Radiation Therapy by Connor Thropp, MS, Jaroslaw Hepel, MD, Timothy Leech, Eric E. Klein, PhD, Qiongge Li, PhD

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Performance of Deep Learning-Based Algorithm for Detection of Pediatric Intussusception on Abdominal Ultrasound Images by Zheming Li, Chunze Song, Jian Huang, Jing Li, Shoujiang Huang, Baoxin Qian, Xing Chen, Shasha Hu, Ting Shu, Gang Yu

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Explainable machine learning algorithm to predict cardiovascular event in patients undergoing peritoneal dialysis by Qiqi Yan, Guiling Liu, Ruifeng Wang, Dandan Li, Xiaoli Chen, Jingjing Cong, Deguang Wang

“…The patients were randomly divided into training and validation sets in a 7:3 ratio. Cox regression, extreme gradient boosting (XGBoost), and random survival forest (RSF) models were developed using the training set and validated using the validation set. …”
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Research on Sleep Staging Based on Support Vector Machine and Extreme Gradient Boosting Algorithm by Wang Y, Ye S, Xu Z, Chu Y, Zhang J, Yu W

“…Yiwen Wang,1 Shuming Ye,2 Zhi Xu,3 Yonghua Chu,1 Jiarong Zhang,4 Wenke Yu5 1Clinical Medical Engineering Department, The Second Affiliated Hospital, Zhejiang University School of Medicine, HangZhou, ZheJiang, People’s Republic of China; 2Department of Biomedical Engineering, Zhejiang University, HangZhou, ZheJiang, People’s Republic of China; 3China Astronaut Research and Training Center, BeiJing, People’s Republic of China; 4Baidu Inc, BeiJing, People’s Republic of China; 5Radiology Department, ZheJiang Province Qing Chun Hospital, HangZhou, ZheJiang, People’s Republic of ChinaCorrespondence: Yiwen Wang; Shuming Ye, Email karenkaren2010@zju.edu.cn; ysmln@vip.sina.comPurpose: To develop a sleep-staging algorithm based on support vector machine (SVM) and extreme gradient boosting model (XB Boost) and evaluate its performance.Methods: In this study, data features were extracted based on physiological significance, feature dimension reduction was performed through appropriate methods, and XG Boost classifier and SVM were used for classification. …”
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Development of an Algorithm for Semantic Segmentation of Earth Remote Sensing Data to Determine Phytoplankton Populations by Yu. V. Belova, I. F. Razveeva, E. O. Rakhimbaeva

“…To automate the detection of phytoplankton distribution areas, a computer vision algorithm based on the U-Net CNN was developed. The model was evaluated by the calculated values of the main quality metrics related to segmentation tasks. …”
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CP-Based SBHT-RLS Algorithms for Tracking Channel Estimates in Multicarrier Modulation Systems by H. Ali

“…Performance of the algorithms is also evaluated for varying forgetting factor parameter values, constellation size, and word lengths. …”
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Reliability of plastid and mitochondrial localisation prediction declines rapidly with the evolutionary distance to the training set increasing. by Sven B Gould, Jonas Magiera, Carolina García García, Parth K Raval

“…Their reliability across evolutionary diverse species is unknown. Here, we evaluate the performance of common algorithms (TargetP, Localizer and WoLFPSORT) for four photosynthetic eukaryotes (Arabidopsis thaliana, Zea mays, Physcomitrium patens, and Chlamydomonas reinhardtii) for which experimental plastid and mitochondrial proteome data is available, and 171 eukaryotes using orthology inferences. …”
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Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error by Jianhui Zhao, Erqian Dong, Mingui Sun, Wenyan Jia, Dengyi Zhang, Zhiyong Yuan

“…A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. …”
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EDUCATIONAL TRAINING SIMULATOR FOR MONITORING READING TECHNIQUE AND SPEED BASED ON SPEECH-TO-TEXT (STT) METHODS by Olesia Barkovska, Heorhii Ivashchenko, Dmytro Rosinskiy, Daniil Zakharov

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Boosting brain-computer interface performance through cognitive training: A brain-centric approach by Ziyuan Zhang, Ziyu Wang, Kaitai Guo, Yang Zheng, Minghao Dong, Jimin Liang

“…Using the rapid serial visual presentation (RSVP)-based BCI, we evaluated the behavioral and electroencephalogram (EEG) decoding performance of subjects before and after cognitive training in high target percentage (with AB) and low target percentage (without AB) surveillance tasks, respectively. …”
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