Effectiveness of Timely Isolation of Patients with Respiratory Infection in a Children's Hospital: a Simulation Study by N. V. Saperkin, L. Ju. Poslova, M. Ju. Kirillin, M. E. Garbuz, O. V. Kovalishena

“…To simulate the anti-epidemic measure, we included in the developed simulation model the execution of a local algorithm of actions by a doctor in the event of detection of a patient with ARVI (50% probability of non-compliance with isolation; almost all sources of infection are isolated; 100% decision-making, the ideal option).Results. …”
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Post-processing of a distributed source method for the localization of somatosensory cortex in a cohort of epilepsy patients by Kevin Tyner, Matthew McCumber, Srijita Das, Carmen Urban, Anthony J. Maxin, Tiffany Chu, Mustaffa Alfatlawi, Stephen V. Gliske

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Influencing factors of cross screening rate and its intelligent prediction model by Lala ZHAO, Feng XU, Chenlong DUAN, Chenhao GUO, Wei WANG, Haishen JIANG, Jinpeng QIAO

“…Based on linear regression (LR), support vector machine (SVM), decision tree (DT) and random forest (RF) algorithms, four intelligent prediction models of cross screening rate were established. …”
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Developing an Interpretable Machine Learning Model for Early Prediction of Cardiovascular Involvement in Systemic Lupus Erythematosus by Deng Z, Liu H, Chen F, Liu Q, Wang X, Wang C, Lyu C, Li J, Li T

“…This study aimed to identify key factors associated with cardiac involvement in SLE and to develop an interpretable machine learning (ML) model for risk prediction.Methods: We conducted a retrospective analysis of 1,023 SLE patients hospitalized in Shenzhen People’s Hospital between January 2000 and December 2021, with a median age of 31 years at hospitalization (IQR: 25– 39 years), 92.1% being female, and 18.77% developing cardiovascular involvement during a median follow-up of 3,737 days (IQR: 1,920– 5,246). The most predictive features were selected through the intersection of three feature selection techniques: Random Forest, LASSO, and XGBoost. …”
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Artificial intelligence based surgical support for experimental laparoscopic Nissen fundoplication by Holger Till, Ciro Esposito, Chung Kwong Yeung, Dariusz Patkowski, Sameh Shehata, Steve Rothenberg, Georg Singer, Tristan Till

“…The results remained robust despite extensive image augmentation. For 3/5 classifiers the results remained identical; detection of incomplete and too loose LNFs showed a slight decline in predictive power.ConclusionThis experimental study demonstrates that an AI/CV algorithm can effectively detect VQIs in digital images of Nissen fundoplications. …”
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Intelligent beehive monitoring system based on internet of things and colony state analysis by Yiyao Zheng, Xiaoyan Cao, Shaocong Xu, Shihui Guo, Rencai Huang, Yingjiao Li, Yijie Chen, Liulin Yang, Xiaoyu Cao, Zainura Idrus, Hongting Sun

“…Moreover, our counting algorithm also achieved excellent results, with root mean square error (RMSE) of 1.3 ± 0.1, 0.2 ± 0.0, and 1.6 ± 0.1 in counting the number of bees current, entry, and out scene in an episode, respectively. …”
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Cluster Policy Based on the Analysis of the Situation in the Municipality by Yu. N. Lapygin, D. V. Tulinova

“…The proposed approach to the formation of cluster policy in the region was implemented in the process of developing development strategies for the three municipalities of the Vladimir region in 2018–2019.…”
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Distribution Network Design for Fixed Lifetime Perishable Products: A Model and Solution Approach by Z. Firoozi, N. Ismail, Sh. Ariafar, S. H. Tang, M. K. A. M. Ariffin, A. Memariani

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Expert Logical аnd Probabilistic Model оf Intellectual Control System by A. V. Gulay, V. M. Zaytsev

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Automatic Determination of Parting Line Locations for Sand-Casting Process Using CAD System by Tama Reza Setiawan Putra, Fariz Muharram Hasby, Isa Setiasyah Toha, Wisnu Aribowo

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Development and validation of an early predictive model for hemiplegic shoulder pain: a comparative study of logistic regression, support vector machine, and random forest by Qiang Wu, Qiang Wu, Fang Zhang, Yuchang Fei, Zhenfen Sima, Shanshan Gong, Qifeng Tong, Qingchuan Jiao, Hao Wu, Jianqiu Gong, Jianqiu Gong

“…The performance parameters (accuracy, precision, recall, and F1 score) of the models were calculated, the receiver operating characteristic curve (ROC) and the decision curve analysis (DCA) were plotted to compare the performance of the three models. …”
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Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis by Gabriela Riemekasten, Felix Nensa, Hanna Grasshoff, René Hosch, Malte Maria Sieren, Lennart Berkel, Jörg Barkhausen, Roman Kloeckner, Franz Wegner

“…An artificial intelligence-based 3D body composition analysis (BCA) algorithm assessed muscle volume, different adipose tissue compartments, and bone mineral density. …”
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A Novel Ensemble Classifier Selection Method for Software Defect Prediction by Xin Dong, Jie Wang, Yan Liang

“…The experimental results demonstrate that the DFD ensemble learning-based software defect prediction model outperforms the ten other models, including five common machine learning (ML) classification algorithms (logistic regression (LR), naïve Bayes (NB), K-nearest neighbor (KNN), decision tree (DT), and support vector machine (SVM)), two deep learning (DL) algorithms (multi-layer perceptron (MLP) and convolutional neural network (CNN)), and three ensemble learning algorithms (random forest (RF), extreme gradient boosting (XGB), and stacking). …”
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MAB-Based Online Client Scheduling for Decentralized Federated Learning in the IoT by Zhenning Chen, Xinyu Zhang, Siyang Wang, Youren Wang

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University proceedings. Volga region. Technical sciences by M.Yu. Babich, V.E. Kuznetsov, M.A. Chigirev, A.M. Babich

Advancing cardiovascular care through actionable AI innovation by Giuseppe Biondi-Zoccai, Arjun Mahajan, Dylan Powell, Mariangela Peruzzi, Roberto Carnevale, Giacomo Frati

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More than a chatbot: a practical framework to harness artificial intelligence across key components to boost digital therapeutics quality by Amit Baumel

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Application of Machine Learning to Statistical Evaluation of Artificial Rainfall Enhancement by Li Dan, Lin Wen, Liu Qun, Feng Hongfang, Hu Shuping, Wang Zhihai

“…In order to evaluate effects of artificial rainfall enhancement objectively and quantitatively, combing linear fitting, polynomial regression, spline regression and 3 other machine learning methods including decision tree, support vector machine and neural network, the relationship model between the rainfall in the target area and the contrast area is established based on rainfall data and operation information of recent 10 years in Fujian. …”
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Optimizing Handover Parameters by Q-Learning for Heterogeneous Radio-Optical Networks by Sihua Shao, Guanxiong Liu, Abdallah Khreishah, Moussa Ayyash, Hany Elgala, Thomas D. C. Little, Michael Rahaim

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Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning by Neng Wang, Shuai Tao, Liang Chen

“…We utilized six machine learning algorithms—Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), K-Nearest Neighbors (KNN), Random Forest (RF), and Decision Tree (DT)—to construct predictive models. …”
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