Automated Calibration of SWMM for Improved Stormwater Model Development and Application by Hossein Ahmadi, Durelle Scott, David J. Sample, Mina Shahed Behrouz

“…Additionally, in the single-objective optimization test case, the model yielded NSE values of 0.68 and 0.73 for the calibration and validation, respectively. The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. …”
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Machine learning for prediction of Helicobacter pylori infection based on basic health examination data in adults: a retrospective study by Qiaoli Wang, Tao Liang, Yuexi Li, Peng Zhou, Xiaoqin Liu

“…Six distinct machine learning algorithms were utilized to construct the predictive models, and their performance was comprehensively evaluated. …”
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RESEARCH OF FACTORS, WHICH MAY LEED TO ECONOMIC EMERGENCY APPEARANCE by O. O. Trush, D. A. Gorovyi, O. M. Goncharenko

“…The authors’ scheme of economic character emergency growth is also suggested. As it can be seen from the scheme, there are two main reasons for the appearance of an emergency, depending on the source of influence on this event — external or internal to the country. …”
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Energy dependence of the response of X-ray multimeter for radiation qualities in mammography by Elisabeth Salomon, Peter Homolka, Istvan Csete, Paula Toroi

“…Ionization chambers or semiconductor-based X-ray multimeters (XMMs) are used to measure these parameters, with XMMs also displaying tube voltage in one exposure in addition to numerous other parameters. …”
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Accuracy is not enough: a heterogeneous ensemble model versus FGSM attack by Reham A. Elsheikh, M. A. Mohamed, Ahmed Mohamed Abou-Taleb, Mohamed Maher Ata

“…Abstract In this paper, based on facial landmark approaches, the possible vulnerability of ensemble algorithms to the FGSM attack has been assessed using three commonly used models: convolutional neural network-based antialiasing (A_CNN), Xc_Deep2-based DeepLab v2, and SqueezeNet (Squ_Net)-based Fire modules. …”
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Boosting grapevine phenological stages prediction based on climatic data by pseudo-labeling approach by Mehdi Fasihi, Mirko Sodini, Alex Falcon, Francesco Degano, Paolo Sivilotti, Giuseppe Serra

“…Moreover, the study shows that the proposed methodology can also be integrated with explainable artificial intelligence techniques to determine the importance of the input features. …”
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Machine learning-based model for CD4+ conventional T cell genes to predict survival and immune responses in colorectal cancer by Zijing Wang, Zhanyuan Sun, Hengyi Lv, Wenjun Wu, Hai Li, Tao Jiang

“…The RS derived from this model was also analyzed for its implications in the TME, and its potential utility in immunotherapy and chemotherapy contexts. …”
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A Novel Dataset for Early Cardiovascular Risk Detection in School Children Using Machine Learning by Rafael Alejandro Olivera Solís, Emilio Francisco González Rodríguez, Roberto Castañeda Sheissa, Juan Valentín Lorenzo-Ginori, José García

“…We conducted a rigorous performance evaluation of 10 machine learning (ML) algorithms to classify cardiovascular risk into two categories: at risk and not at risk. …”
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Intelligent assessment of damage and prediction of seismic damage spectrum under the effect of Near-Fault earthquakes in Iran by R. Fazli, M. Shamekhi Amiri, H. Pahlavan

“…Predicting seismic damage spectra and capturing both structural and earthquake features are crucial for the design of new buildings and also for the resilience evaluation of existing ones. …”
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BlendNet: a blending-based convolutional neural network for effective deep learning of electrocardiogram signals by S. Premanand, Sathiya Narayanan

“…First, the 1-D ECG signal is converted into a scalogram image using CWT, and a binary version of the scalogram image is also obtained. Then, both the scalogram and binary images are subjected to a sequence of convolution and pooling layers, and the resulting feature images are blended. …”
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Modern strategies of alternative insulin delivery systems by І. О. Vlasenko, L. L. Davtian, V. V. Hladyshev

“…The use of insulin in the form of alternative delivery systems may also be promising in the prevention of type 1 diabetes and other diseases.…”
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Investigating ethical tradeoffs in crisis standards of care through simulation of ventilator allocation protocols. by Jonathan Herington, Jessica Shand, Jeanne Holden-Wiltse, Anthony Corbett, Richard Dees, Chin-Lin Ching, Margie Shaw, Xueya Cai, Martin Zand

“…Unlike other protocols, the New York and Maryland algorithms did not generate significant disparities in lives saved and life-years saved between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations. …”
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Identification of marker genes associated with oxidative stress in hypertrophic cardiomyopathy using bioinformatics analysis and experimental validation by Jian Zhuo, Ding Ding, Mengkang Fan, Weiwei Lu, Xiaochen Lu, Lihong Yao, Hongzhuan Sheng

“…After differential analysis, marker genes were obtained using LASSO and SVM-RFE algorithms. DAVID was used, along with the GSVA and GSEA packages to perform gene ontology, pathway function enrichment, and gene set enrichment analyses. …”
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Antiviral therapy can effectively suppress irAEs in HBV positive hepatocellular carcinoma treated with ICIs: validation based on multi machine learning by Shuxian Pan, Zibing Wang

“…Predictive models were constructed using three machine learning algorithms to analyze and statistically evaluate clinical characteristics, including immune cell data. …”
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A Novel Tool for Biodiversity Studies: Earthworm Classification via NGS and Neural Networks by Tadeusz Malewski, Ewa Ropelewska, Andrzej Skwiercz, Anastasiia Lutsiuk, Anita Zapałowska

“…All earthworms were correctly classified. Also, in the case of other models, earthworm classes were distinguished with high accuracies, such as 99% (Naive Bayes, Random Forest, SVM, KNN), 97% (Simple Logistic), and 94% (KStar). …”
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Evaluation of Modified Reflection Symmetry Decomposition Polarization Features for Sea Ice Classification by Tianlang Lan, Chengfei Jiang, Xiaofan Luo, Wentao An

“…Three machine learning algorithms, Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machines (SVM), were also used for the comparative analysis. …”
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Enhancing Healthcare With WBAN and Digital Twins: A Machine Learning Approach for Predictive Health Monitoring by Rishit Mahapatra, Deepak Sethi, Kaushik Mishra

“…The RF model scored highest across all measurements, with accuracy (97%), precision (98%), recall (97%), F1 score (98%), ROC AUC score (97%), and cross-validation accuracy (97%). XGB and SVC also performed strongly, with GB, Ba, ET, and AB ranking high in efficiency, with consistent scores in the mid-90s. …”
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Unsupervised Rural Flood Mapping from Bi-Temporal Sentinel-1 Images Using an Improved Wavelet-Fusion Flood-Change Index (IWFCI) and an Uncertainty-Sensitive Markov Random Field (US... by Amin Mohsenifar, Ali Mohammadzadeh, Sadegh Jamali

“…The IWFCI modifies the mean-ratio change index (CI) to fuse it with the log-ratio CI using the discrete wavelet transform (DWT). The IWFCI also employs a discriminant feature derived from the co-flood image to enhance the separability between the non-flood and flood areas. …”
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Development and Analysis of Patient-Based Complete Conducting Airways Models. by Rafel Bordas, Christophe Lefevre, Bart Veeckmans, Joe Pitt-Francis, Catalin Fetita, Christopher E Brightling, David Kay, Salman Siddiqui, Kelly S Burrowes

“…These models have typically been used for mechanistic studies, but also have the potential to be used in a patient-specific setting. …”
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Ethical Aspects of the Influence of Neural Networks on the Lives of Students in the Context of a Sociological Approach (using the Example of Students of the IT Department of ETU) by A. S. Kurapova, S. V. Kurapov, A. D. Derzhavina, N. V. Shatilo

“…To ensure the ethical and safe use of these technologies, it is recommended to increase the transparency of algorithms, provide user training, and develop ethical standards and regulations for their use.…”
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