SELECTION OF RECIPIENTS FOR HEART TRANSPLANTATION BASED ON URGENCY STATUS by O. A. Sujayeva, M. I. Davidovitch, S. G. Sudzhaeva, Y. P. Оstrovsky

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Research on Tracking Control of Unmanned Mine Trucks Based on Adaptive Preview by HUANG Yaoran, LIU Zhicong, KANG Yuanrong

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Applying PageRank to Team Ranking in Single-Elimination Tournaments: Evidence from Taiwan’s High School Baseball by Yu-Chia Hsu, Wen-Jie Zhang

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An extension of the Spiegelhalter-Knill-Jones method for continuous covariates in clinical decision making by Bart K. M. Jacobs, Tafadzwa Maseko, Lutgarde Lynen, Aquiles Rodrigo Henriquez-Trujillo, Jozefien Buyze

Subjects: “…Prediction…”
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DEVELOPING PREDICTIVE MODELS OF INTERNET SERVICE STRATEGIES by Maxim Yu. Khramov

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<p><strong>Evaluation of geostatistical method and hybrid artificial neural network with imperialist competitive algorithm for predicting distribution pattern of <em>Tetranychus</em> <em>urticae</em> (Acari: Tetranychidae) in cucumber field of Behbahan, Iran</strong></p> by Alireza Shabaninejad, Bahram Tafaghodinia, Nooshin Zandi-Sohani

“…In Geostatistics methods ordinary kriging, and ANN with imperialist competitive algorithm were evaluated. Comparison of ANN and geostatistical showed that ANN capability is more than ordinary kriging method so that the ANN predicts distribution of this pest dispersion with 0.98 coefficient of determination and 0.0038 mean squares errors lower than the Geostatistical methods. …”
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Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning by TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng

“…There are many influencing factors and difficulty in the prediction of total organic carbon content, so it is particularly important to explore the most suitable high-precision prediction method for the prediction of total organic carbon content in this area. …”
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Research on the prediction of blasting fragmentation in open-pit coal mines based on KPCA-BAS-BP by Shuang Liu, Enxiang Qu, Chun LV, Xueyuan Zhang

“…Compared with the unoptimized BP neural network and the BP neural network optimized by the artificial bee colony algorithm (ABC) model, this model has higher prediction accuracy and is more suitable for predicting the blasting block size of open-pit coal mines, it provides a new method for predicting the fragmentation of blasting under the influence of multiple factors, filling the gap in related theoretical research, and has certain practical application value.…”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. …”
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Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges by Ebenezer Afrifa‐Yamoah, Eric Adua, Emmanuel Peprah‐Yamoah, Enoch O. Anto, Victor Opoku‐Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi

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Prediction of CO2 emission for the central European countries through five metaheuristic optimization techniques helping multilayer perceptron by Hossein Moayedi, Azfarizal Mukhtar, Serhan Alshammari, Mohamed Boujelbene, Isam Elbadawi, Quynh T Thi, Mojtaba Mirzaei

“…To develop a reliable predictive network considering the problem complexity, multilayer perceptron (MLP) is combined with several nature-inspired optimization algorithms, namely, black hole algorithm (BHA), future search algorithm (FSA), backtracking search algorithm (BSA), biogeography-based optimization (BBO), and shuffled complex evolution (SCE). …”
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Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning by Jiayuan Xu, Andrew J. Doig, Sofia Michopoulou, Sofia Michopoulou, Petroula Proitsi, Petroula Proitsi, Fumie Costen, The Alzheimer's disease neuroimaging initiative

“…This study aims to develop and validate machine learning algorithms for accurately predicting brain Aβ positivity using plasma biomarkers, genetic information, and clinical data as a cost-effective alternative to PET imaging.MethodsWe analyzed 1,043 patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and validated our models on 127 patients from the Center for Neurodegeneration and Translational Neuroscience (CNTN) dataset. …”
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Predictive modeling of asthma drug properties using machine learning and topological indices in a MATLAB based QSPR study by Jalal Hatem Hussein Bayati, Abid Mahboob, Laiba Amin, Muhammad Waheed Rasheed, Abdu Alameri

“…This study utilizes MATLAB program-based algorithms to calculate topological indices and machine learning algorithms to explore their ability to predict the physio-chemical properties of asthma drugs. …”
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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

Subjects: “…Arrhythmia prediction…”
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Constant time lattice reduction in dimension 4 with application to SQIsign by Otto Hanyecz, Alexander Karenin, Elena Kirshanova, Péter Kutas, Sina Schaeffler

“… In this paper we propose a constant time lattice reduction algorithm for integral dimension-4 lattices. …”
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Ensemble-Based Neighborhood Attribute Reduction: A Multigranularity View by Yuan Gao, Xiangjian Chen, Xibei Yang, Pingxin Wang, Jusheng Mi

“…Different from traditional process which computes reduct through employing a fixed granularity, our algorithm aims to obtain reduct from the viewpoint of multigranularity. …”
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Reduction of artifacts associated with missing data in coherent diffractive imaging by Erik Malm, Yuriy Chushkin

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Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique by Punita Panwar, Sandeep Chaurasia, Jayesh Gangrade, Ashwani Bilandi, Dayananda Pruthviraja

“…In order to address the limitation of time and expedite the diagnostic process, deep learning algorithms have been implemented in the medical field. …”
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Adaptive Receiver-Window Adjustment for Delay Reduction in LTE Networks by N. D. Adesh, A. Renuka

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Interpretable prognostic modeling for long-term survival of Type A aortic dissection patients using support vector machine algorithm by Hao Cai, Yue Shao, Xuan-yu Liu, Chang-ying Li, Hao-yu Ran, Hao-ming Shi, Cheng Zhang, Qing-chen Wu

“…Abstract Objectives This study aims to develop a reliable and interpretable predictive model for long-term survival in Type A aortic dissection (TAAD) patients, utilizing machine learning (ML) algorithms. …”
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