Intracranial stenosis prediction using a small set of risk factors in the Tromsø Study by Luca Bernecker, Liv-Hege Johnsen, Torgil Riise Vangberg

“…Furthermore, the results demonstrate the predictive potential of limited risk factors, highlighting its potential contribution to a multi-modular classification algorithm based on MRAs.…”
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A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

Subjects: “…dam deformation prediction…”
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Comparative analysis of machine learning techniques in metabolomic-based preterm birth prediction by Ying-Chieh Han, Jane Shearer, Chunlong Mu, Donna M. Slater, Suzanne C. Tough, Gavin E. Duggan

“…This study investigated several ML models' efficacy in predicting preterm birth using untargeted metabolomics from serum collected during the third trimester of gestation. …”
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Machine Learning and Medical Data: Predicting ICU Mortality and Re-admission Risks by Runia Roy, Ulya Bayram

“…These studies reduce the problem into a binary task of predicting mortality or re-admission only. However, this is unrealistic since both outcomes are highly possible for each patient. …”
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Improved machine learning framework for prediction of phases and crystal structures of high entropy alloys by Debsundar Dey, Suchandan Das, Anik Pal, Santanu Dey, Chandan Kumar Raul, Pritam Mandal, Arghya Chatterjee, Soumya Chatterjee, Manojit Ghosh

“…The important features were selected using the Pearson correlation coefficient matrix, followed by using of five distinct boosting algorithms to predict phases and crystal structures. …”
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A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…This study introduces the hybrid of the Bayesian optimization algorithm and support vector regression (BOA-SVR) models to predict the removal of aerobic organic (total chemical oxygen demand, COD) and nitrogen compounds such as total Kjeldahl Nitrogen (TKN), ammonium nitrogen (NH4-N), and nitrate nitrogen (NO3-N) from municipal wastewater in a gas-liquid-solid circulating fluidized bed (GLSCFB) bioreactor. …”
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Predicting regional tau accumulation with machine learning‐based tau‐PET and advanced radiomics by Saima Rathore, Ixavier A. Higgins, Jian Wang, Ian A. Kennedy, Leonardo Iaccarino, Samantha C. Burnham, Michael J. Pontecorvo, Sergey Shcherbinin

“…Tau prediction in lobar/global regions benefits from diverse multimodal features. …”
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IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks by Suma Christal Mary Sundararajan, Yamini Bhavani Shankar, Sinthia Panneer Selvam, Nalini Manogaran, Koteeswaran Seerangan, Deepa Natesan, Shitharth Selvarajan

Subjects: “…Water quality prediction…”
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Artificial intelligence-based forecasting models for integrated energy system management planning: An exploration of the prospects for South Africa by Senthil Krishnamurthy, Oludamilare Bode Adewuyi, Emmanuel Luwaca, Mukovhe Ratshitanga, Prathaban Moodley

Subjects: “…Artificial intelligence-based predictive analytics…”
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Prediction of Solar Radiation Data for Garlic Production in Magelang Regency Using Long Short-Term Memory by Muhammad Safrul Safrudin, Imas Sukaesih Sitanggang, Hari Agung Adrianto, Syarifah Aini

“…This study aims to determine the optimal solar radiation for garlic growth using the Long Short-Term Memory (LSTM) algorithm. This algorithm was selected due to its ability to analyze time-series data and predict long-term patterns. …”
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A machine learning-based method for predicting the shear behaviors of rock joints by Liu He, Yu Tan, Timothy Copeland, Jiannan Chen, Qiang Tang

“…In this study, machine learning prediction models (MLPMs), including artificial neural network (ANN), support vector regression (SVR), K-nearest neighbors (KNN), and random forest (RF) algorithms, were developed to predict the peak shear stress values and shear stress-displacement curves of rock joints. …”
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Decision-Making Model for Life Cycle Management of Aircraft Components by Igor Kabashkin, Vitaly Susanin

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Association of weight-adjusted waist index and body mass index with chronic low back pain in American adults: a retrospective cohort study and predictive model development based on machine learning algorithms (NHANES 2009–2010) by Weiye Zhang, Weiye Zhang, Yan Li, Pengwei Shao, Yuxuan Du, Ke Zhao, Jiawen Zhan, Lee A. Tan

“…Six machine learning algorithms were employed to predict CLBP occurrence and identify the optimal algorithm.ResultsA total of 4,687 participants were included. …”
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Prediction of Influence of Environmental Factors on the Toxicity of Pentachlorophenol on <i>E. coli</i>-Based Bioassays by Sulivan Jouanneau, Gerald Thouand

“…This study addresses this challenge by aiming to develop an algorithm capable of predicting the effect of environmental conditions on the impact of a toxicant, pentachlorophenol (PCP). …”
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Correction of Disturbances Influence on Results of Elongated Objects's Probe Microscopy Using Predictive Relief Estimates by P. V. Gulyaev

“…The peculiarity of predictive images is the sharpening of areas distorted by disturbances. …”
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A study on predicting the risk of coronary artery disease in OSAHS patients based on a four-variable screening tool potential predictive model and its correlation with the severity... by Yanli Yao, Yu Li, Yulan Chen, Xuan Qiu, Gulimire Aimaiti, Ayiguzaili Maimaitimin

“…A comprehensive analysis utilizing the random forest machine learning algorithm demonstrated that the AHI exhibits the highest predictive value. …”
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A Study on the Application of Explainable AI on Ensemble Models for Predictive Analysis of Chronic Kidney Disease by K. M. Tawsik Jawad, Anusha Verma, Fathi Amsaad, Lamia Ashraf

“…The goal of this research is to first develop an accurate ensemble model for prediction of unseen cases of CKD given the biomarkers. …”
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A multifaceted comparative analysis of incremental dynamic and static pushover methods in bridge structural assessment, integrated with artificial neural network and genetic algori... by Ashwini Satyanarayana, V. Sindura, L. Geetha, Rakesh Kumar, Mohd Asif Shah, Mary Subaja Christo

“…The results of static pushover analysis and incremental dynamic analysis (IDA) are predicted and compared in this work using ANN and GA, which offers a deeper understanding of their predictive capabilities.…”
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Predictive direct control strategy of unified power quality conditioner based on power angle control by Guifeng Wang, Zewen Wu, Zhan Liu

“…This approach simplifies the controller structure and alleviates the control algorithm’s complexity. Based on a detailed analysis of the PAC mechanism, an instantaneous power angle determination method is proposed based on the reactive power equalization technique, and a predictive direct control strategy given the current generation mechanism is constructed for the series and shunt sides of the UPQC, considering the active power balance of the UPQC system and the principle of constant load fundamental voltage amplitude. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…This study uses a nonlinear model predictive controller (MPC) to ensure accurate trajectory tracking of a four-wheel drive, four-wheel steer (4WD-4WS) mobile robot. …”
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