Post-extrasystolic variation of ST segment and T wave as a mortality risk predictor after myocardial infarction by Ralf J. Dirschinger, Ralf J. Dirschinger, Alexander Müller, Petra Barthel, Alexander Steger, Michael Dommasch, Axel Bauer, Karl-Ludwig Laugwitz, Georg Schmidt, Daniel Sinnecker, Daniel Sinnecker

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Excavating trajectory planning of electric shovel based on dynamic excavating volume prediction by Juan Wu, Rui Liu, Baoguo Lin

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Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey by Beminate Lemma Seifu, Angwach Abrham Asnake, Alemayehu Kasu Gebrehana

“…Maternal unemployment had the most significant positive impact (+0.060) on predicting zero-dose children. Lack of maternal education was the second most significant positive factor (+0.048), indicating that mothers without formal education are more likely to have zero-dose children. …”
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Reductions of GKZ systems and applications to cosmological correlators by Thomas W. Grimm, Arno Hoefnagels

“…These simpler subsystems can then be solved separately resulting in solutions for the full system. The algorithm makes it possible to check when reductions happen and allows for finding the associated simpler solutions. …”
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A new algorithm to assess the risk of malignancy in premenopausal patients with pelvic mass by M. S. Katsyuba, R. Sh. Khasanov, T. I. Madzhidov, G. Z. Muratova, G. A. Usmanova, A. F. Akhmetzyanova, A. Rakhimbekova, V. V. Terentyeva, G. R. Fakhrutdinova

Subjects: “…risk of ovarian malignancy algorithm…”
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Rolling Bearing with Isometric Feature Mapping and Fuzzy C means Fault Identification Method by WANG Ya-ping, LI Shi-song, GE Jiang-hua, XU Di, LI Yun-fei

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Habit Predicting Higher Education EFL Students’ Intention and Use of AI: A Nexus of UTAUT-2 Model and Metacognition Theory by Shaista Rashid

“…With the emergence of AI technology, its adoption in higher education has become an interesting field for researchers. …”
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Establishment of predictive models for postoperative delirium in elderly patients after knee/hip surgery based on total bilirubin concentration: machine learning algorithms by Shuhui Hua, Chuan Li, Yuanlong Wang, YiZhi Liang, Shanling Xu, Jian Kong, Hongyan Gong, Rui Dong, Yanan Lin, Xu Lin, Yanlin Bi, Bin Wang

“…In addition, the SHAP method determines that age and education are the main determinants that affect the prediction of ML models. …”
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Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

“…Accurately predicting key engineering properties, such as compressive and tensile strength, remains a significant challenge in high-performance concrete (HPC) due to its complex and heterogeneous composition. …”
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Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

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Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms by Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, Ana Sanches Silva, Carla Brites

“…This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric algorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). …”
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Construction and validation of a predictive model for suicidal ideation in non-psychiatric elderly inpatients by Shuyun Xiong, Dongxu Si, Meizhu Ding, Cuiying Tang, Jinling Zhu, Danni Li, Ying Lei, Lexian Huang, Xiaohua Chen, Jicai Chen

Subjects: “…Machine learning algorithms…”
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Intelligent Photolithography Corrections Using Dimensionality Reductions by Parag Parashar, Chandni Akbar, Tejender S. Rawat, Sparsh Pratik, Rajat Butola, Shih H. Chen, Yung-Sung Chang, Sirapop Nuannimnoi, Albert S. Lin

“…In this work, we use dimensionality reduction (DR) algorithms to reduce the computation time of complex OPC/EPC problems while the prediction accuracy is maintained. …”
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Sparse sufficient dimension reduction for directional regression by Gayun Kwon, Gijeong Noh, Kyongwon Kim

“…Abstract Sufficient dimension reduction has emerged as a powerful tool for extracting meaningful information within high dimensional datasets over the past few decades. …”
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A Data-Driven Strategy for Long-Term Agrarian Sustainability using the Application of Machine Learning Algorithms to Predictive Models for Pest and Disease Management by Almusawi Muntather, Ameer S. Abdul, Lalitha Yaragudipati Sri

“…PDM-MLA based on predictive modeling predicts infestations with high accuracy by analyzing weather, parameters of soil, history of outbreaks of pests, and crop health data. …”
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Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

“…The sensitivity assessment approves that the training and generalization abilities of the ELM and ANFIS models for the CS prediction of FRC are improved by their integration with the GWO algorithm. …”
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Pore size classification and prediction based on distribution of reservoir fluid volumes utilizing well logs and deep learning algorithm in a complex lithology by Hassan Bagheri, Reza Mohebian, Ali Moradzadeh, Behnia Azizzadeh Mehmandost Olya

“…Subsequently, the CUDA Deep Neural Network Long Short-Term Memory algorithm(CUDNNLSTM), belonging to the category of DL algorithms and harnessing the computational power of GPUs, is employed for the prediction of CBW, BVI, and FFV logs. …”
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Using Supervised Machine Learning Algorithms to Predict Bovine Leukemia Virus Seropositivity in Florida Beef Cattle: A 10‐Year Retrospective Study by Ameer A. Megahed, Y. Reddy Bommineni, Michael Short, João H. J. Bittar

“…Objectives To compare six different supervised machine‐learning (SML) algorithms used to identify the most important risk factors for predicting BLV seropositivity in beef cattle in Florida. …”
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Predicting higher risk factors for COVID-19 short-term reinfection in patients with rheumatic diseases: a modeling study based on XGBoost algorithm by Yao Liang, Siwei Xie, Xuqi Zheng, Xinyu Wu, Sijin Du, Yutong Jiang

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Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia-A retrospective cohort study. by Wenshan Li, Luke Turcotte, Amy T Hsu, Robert Talarico, Danial Qureshi, Colleen Webber, Steven Hawken, Peter Tanuseputro, Douglas G Manuel, Greg Huyer

“…<h4>Conclusions and implications</h4>We developed an algorithm to predict time to LTC entry among individuals living with dementia. …”
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