Correlation between shapes and sizes of dentofacial arches and their stable parameters by E. G. Vedeshina, D. A. Domenyuk, S. V. Dmitrienko

“…The study proposed an algorithm for determining the optimised predicted individual parameters of dental arches in people with abnormal shapes and sizes of dentofacial arches. …”
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An artificial intelligence approach for prognosis of COVID-19 course in hospitalized patients by T. L. Karonova, I. N. Korsakov, A. A. Mikhailova, D. I. Lagutina, A. T. Chernikova, М. A. Vashukova, M. A. Smolnikova, D. A. Gusev, A. O. Konradi, E. V. Shlyakhto

“…Aim. To create algorithm and risk calculator for predicting the lethal outcome in patients with COVID-19.Materials and methods. …”
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Proactive Frequency Stability Scheme Based on Bayesian Filters and Spectral Clustering by Gian Paramo, Mario D. Baquedano-Aguilar, Arturo Bretas, Sean Meyn

“…In this work, phasor measurement units are used to predict frequency values. When a disturbance is detected, the state of frequency is predicted a few seconds into the future via a particle filter algorithm. …”
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An Evolutionary Formulation of the Crossing Number Problem by Che Sheng Gan, Wee Chiat Alan Tan, Voon Chet Koo, Kwang Hwai Mak

“…It is shown that the EA implementation provides good confirmation of the predicted crossing numbers.…”
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The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer. by Saliha Ece Acuner Ozbabacan, Attila Gursoy, Ruth Nussinov, Ozlem Keskin

“…In the reconstructed pathway there are 104 interactions between proteins whose three dimensional structures are experimentally identified; only 15 have experimentally-determined structures of the interacting complexes. By predicting the protein-protein complexes throughout the pathway via the PRISM algorithm, the structural coverage increases from 15% to 71%. …”
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Effects of Polypropylene Waste Addition as Coarse Aggregates in Concrete: Experimental Characterization and Statistical Analysis by D. C. Naveen, K. Naresh, B. S. Keerthi Gowda, Madhu Sudana Reddy G, C. Durga Prasad, Ragavanantham Shanmugam

“…The Levenberg–Marquardt algorithm was used in predicting the mechanical properties using the ANN. …”
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A Dynamic Branch-Switching Method for Parametrically Excited Systems by A.Y.T. Leung, T. Ge

“…The branch-switching algorithm in static is applied to steady state dynamic problems. …”
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Modeling the Relationship Between Radon Anomalies and Seismic Activity Using Artificial Neural Networks and Statistical Methods by Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva

“…The methodology includes wavelet transformation for noise removal, a multilayer ANN trained using the Levenberg–Marquardt algorithm, and a segmentation approach based on radial zones (annuli) for localized predictions. …”
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PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD by Fathu Nurrahman, Hari Wijayanto, Aji Hamim Wigena, Nunung Nurjanah

“…Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and SMOTE to help improve the performance of the classification model in predicting a particular class. After the data pre-processing process is carried out, classification modeling will be carried out using the XGBoost algorithm. …”
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Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0) by J. W. Marschalek, E. Gasson, T. van de Flierdt, C.-D. Hillenbrand, M. J. Siegert, M. J. Siegert, L. Holder

“…These results show that the algorithm could be used to predict the provenance signature of past ice sheet configurations. …”
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Multiclass Classification of Solar Flares in Imbalanced Data Using Ensemble Learning and Sampling Methods by Haodi Jiang, Ryoma Matsuura, Jason T. L. Wang

“…They are categorized into four classes: B, C, M, and X, depending on their intensity, with X-class flares being the strongest. Being able to predict a flare’s class before its occurrence is critical for anticipating the severity of its impact on Earth. …”
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A 3D Image Reconstruction Model for Long Tunnel Geological Estimation by Yongtao Liu, Jie Qiao, Tianyuan Han, Longhui Li, Ting Xu

“…To ensure personnel safety, the geological characteristics must be predicted before tunnel face excavation. In this study, the ground-penetrating radar (GPR) technique is introduced to obtain information regarding the tunnel excavation face at a certain interval. …”
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Assessing the potential of a Bayesian ranking as an alternative to consensus meetings for decision making in research funding: A case study of Marie Skłodowska-Curie actions. by Rachel Heyard, David G Pina, Ivan Buljan, Ana Marušić

“…While we set out to understand if algorithmic approaches, with the aim of summarising individual evaluation scores, could replace consensus meetings, we concluded that currently individual scores assigned prior to the consensus meetings are not useful to predict the final funding outcomes of the proposals. …”
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Motion and Inertia Estimation for Non-Cooperative Space Objects During Long-Term Occlusion Based on UKF-GP by Rabiul Hasan Kabir, Xiaoli Bai

“…In particular, we implement the multi-output GP to predict the projection measurements of a stereo-camera system onboard a chaser spacecraft. …”
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Crucial heat damage analysis and optimization of a mid-sized pickup truck based on a deep Gaussian process model by Zebin Zhang, Sisi Liu, Xianzong Meng, Tingting Wang, Shizhao Jing, Chuanrui Wang, Dongchen Qin

“…Based on simulation results, a multi-objective two-layer deep Gaussian process model predicted heat source temperatures. The positions of cooling components were optimized using a genetic algorithm with heat-sensitive locations as the objectives. …”
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Calibration and uncertainty quantification for deep learning-based drought detection by Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls

“…To address this shortcoming, we introduce methodologies for model calibration and entropy-based uncertainty quantification for deep learning-based drought detection. The calibration algorithm can deal with calibration errors by reducing distributional shifts and alleviating overconfident predictions. …”
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Machine learning developed immune-related exosome signature for prognosis and immunotherapy benefit in bladder cancer by Xiaoting Luo, Yi Luo

“…To investigate the performance of IES in predicting the immunotherapy benefit, three immunotherapy datasets (GSE91061, GSE78220 and IMvigor210) and several predicting scores were used. …”
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FORECASTING COHERENT VOLATILITY BREAKOUTS by A. S. Didenko, M. M. Dubovikov, B. A. Poutko

“…The paper develops an algorithm for making long-term (up to three months ahead) predictions of volatility reversals based on long memory properties of financial time series. …”
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ABC and HML-methods application for determination and optimization of stock for electrical equipment accessory parts by A. V. Beloglazov, A. G. Rusina, O. V. Fomenko, D. A. Pekhota, V. A. Fyodorova

“…To describe the use of ABC and HML-methods for predicting the volume of emergency stock for main electrical equipment accessory parts. …”
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A Few-shot Learning Method for Intent Analysis of Air Combat Confrontation Behaviors by PAN Ming, ZHENG Jingsong, LI Jinliang, FANG Long, YANG Yang, ZHAO Shijie

“…The experimental simulation results show that the accuracy of the few-shot contrastive learning algorithm based on data augmentation in predicting the behavior intention of few-shot air combat targets is 91. 13% .…”
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