Search Results - evaluation algorithms

Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of resampling strategies and classifiers for imbalanced classification tasks. …”
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Dynamic Optimization of Recurrent Networks for Wind Speed Prediction on Edge Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Muhammad Asim, Samia Allaoua Chelloug, Mohammed A. ELAffendi

“…Evaluations on wind datasets from Chile, Kazakhstan and Mongolia demonstrate that aSAR-optimized models reduce prediction errors by up to 54.17% and decrease MS by 98.75% relative to state-of-the-art techniques. …”
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Lumen Degradation Lifetime Prediction for High-Power White LEDs Based on the Gamma Process Model by Mesfin Seid Ibrahim, Jiajie Fan, Winco K.C. Yung, Zeyu Wu, Bo Sun

“…The MLE method has shown superiority over MM in terms of the estimation of the model parameters due to its iterative algorithm being likely to find the optimal estimation. …”
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Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance by Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen-Quan Tao

“…The GSA module uses the Sobol method to evaluate the impact of design variables on performance. …”
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A Hybrid Multi-Criteria Decision-Making and Multi-Objective Framework for Optimal Sizing of PV-Powered EV Charging Station With Battery Storage by Soumya Sathyan, V. Ravikumar Pandi, Preetha Sreekumar, Nishant Thakkar, Surender Reddy Salkuti

“…The proposed framework was implemented using MATLAB, which enabled efficient development and testing of the algorithm. Three case studies were conducted to evaluate the influence of Analytic Hierarchy Process (AHP) derived weights on the system design obtained using the proposed framework. …”
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Organizational and technological level of major repairs of buildings and structures by Liya D. Mailyan, Nikolay O. Sizen

“…The study allowed to systematize organizational and technological problems of major repairs; to define the factors influencing the organizational and technological level of major repairs of buildings (structures); to propose a model for its determination; to identify the characteristics of the factors influencing it; to develop a formula for evaluating the organizational and technological level of major repairs; to propose an algorithm for estimation the general organizational and technological level of major repairs; to derive, using a practical example, the significance of the factors influencing the execution quality of major repairs; to give proposals for improving the organizational and technological level of major repairs.Discussion and conclusions. …”
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Development and Validation of a Machine Learning Model for Predicting Long-Term Depression Risk in ACS Patients After PCI: A Retrospective Cohort Study by Lv H, Sun F, Zhang Y, Zhou X

“…Feature selection was conducted using the Boruta algorithm, and restricted cubic spline (RCS) analysis was applied to assess non-linear associations. …”
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Clinical Justification for Preliminary Thermal Exposure to Composite in the Treatment of Caries: Randomized Clinical Trial by U. A. Shipieva, A. A. Adamchik, A. A. Gushchin, V. N. Samhaev, K. D. Kirsh, M. A. Adamchik, N. O. Risovannaya

“…The quality of composite restorations within the clinical study was evaluated using the modified Ryge criterion immediately after treatment and after 6, 12, 18, 24 months. …”
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A radiomics approach for predicting gait freezing in Parkinson’s disease based on resting-state functional magnetic resonance imaging indices: A cross-sectional study by Miaoran Guo, Hu Liu, Long Gao, Hongmei Yu, Yan Ren, Yingmei Li, Huaguang Yang, Chenghao Cao, Guoguang Fan

“…Neurological and clinical characteristics were also evaluated. We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators. …”
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Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis by Liping Tang, Dong Pang, Chengbang Wang, Jiali Lin, Shaohua Chen, Jiangchun Wu, Junqi Cui

“…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …”
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Identification of plasma microRNAs as new potential biomarkers with high diagnostic power in human cutaneous melanoma by Stefano Fogli, Beatrice Polini, Sara Carpi, Barbara Pardini, Alessio Naccarati, Nevio Dubbini, Maria Lanza, Maria Cristina Breschi, Antonella Romanini, Paola Nieri

“…Data analysis was performed using global mean normalization and NormFinder algorithm. Linear regression followed by receiver operating characteristic analyses was carried out to evaluate whether selected plasma miRNAs were able to discriminate between cases and controls. …”
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Priority Development Subject Areas of Global Medical Science by K. Yu. Tarkhov

“…The method is actively and widely used not only for rating models based on various bibliometric indicators and parameters, as well as for evaluating the publication activity of authors, organizations, scientific publications, cities, and countries. …”
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Innovative IoT-enabled mask detection system: A hybrid deep learning approach for public health applications by Parul Dubey, Vinay Keswani, Pushkar Dubey, Gunjan Keswani, Dhananjay Bhagat

“…The proposed framework integrates ResNet50 and MobileNetV2 architectures, optimized using the Adaptive Flame-Sailfish Optimization (AFSO) algorithm. This hybrid approach enhances detection accuracy and computational efficiency, making it suitable for real-time deployment. …”
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Deep learning approach for survival prediction for patients with synovial sarcoma by Ilkyu Han, June Hyuk Kim, Heeseol Park, Han-Soo Kim, Sung Wook Seo

“…We developed a novel deep-learning-based prediction algorithm for survival rates of synovial sarcoma patients. …”
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Choice of ventricular arrhythmia therapy in coronary artery disease by A. A. Tatarinova, E. A. Ryngach, T. V. Treshkur

“…To study trigger factors of ventricular arrhythmias (VA) in patients with stable coronary artery disease (CAD) and evaluate the effectiveness of individualized treatment.Material and methods. …”
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The Current Role and Prospects of Electrophysiological Research Methods in Ophthalmology. Literature Review by V. N. Kazajkin, V. O. Ponomarev, A. V. Lizunov, A. E. Zhdanov, A. Yu. Dolganov, V. I. Borisov

“…This leaves the possibility and the need for the study, optimization and algorithmization of the assessment data of the differentiated criteria inherent for a particular ocular pathology. …”
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Racial disparities in continuous glucose monitoring-based 60-min glucose predictions among people with type 1 diabetes. by Helene Bei Thomsen, Livie Yumeng Li, Anders Aasted Isaksen, Benjamin Lebiecka-Johansen, Charline Bour, Guy Fagherazzi, William P T M van Doorn, Tibor V Varga, Adam Hulman

“…Potential healthcare disparities can happen when machine learning models, used in diabetes technologies, are trained on data from primarily White patients. We aimed to evaluate algorithmic fairness in glucose predictions. …”
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Multiparametric ultrasound liver examination in cardiological overweight patients: determining the cause of fibrosis and severity of steatosis by D. Yu. Shestakova, A. V. Borsukov, A. I. Skutar, A. R. Akhmedova

“…Aim. To evaluate the feasibility of using multiparametric liver ultrasound to determine the pathophysiological causes of increased stiffness in patients with cardio-metabolic risks.Material and methods. …”
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Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis by Yang Qi, Zheng Shijin, Xie Suzhen, Feng Enmin

“…By considering the nonlinear characteristics of the enzymatic-catalytic system as a primary constraint, we formulate a robust optimal control model that simultaneously evaluates the production efficiency of 1,3-PD and its sensitivity to uncertain parameters. …”
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Inverse Modeling for Subsurface Flow Based on Deep Learning Surrogates and Active Learning Strategies by Nanzhe Wang, Haibin Chang, Dongxiao Zhang

“…Several subsurface flow problems, including both single‐phase groundwater flow and two‐phase (oil‐water) flow problems, are introduced to evaluate the performance of the proposed active learning strategies. …”
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