Investigating the contributory factors influencing speeding behavior among long-haul truck drivers traveling across India: Insights from binary logit and machine learning technique... by Balamurugan Shandhana Rashmi, Sankaran Marisamynathan

“…The analysis results showed that RF demonstrated superior performance in predicting speeding behavior over other competing algorithms with accuracy (0.80), F1 score (0.77), and AUROC (0.81). …”
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Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study by Mengting Gu, Wenjie Zou, Huilin Chen, Ruilin He, Xingyu Zhao, Ningyang Jia, Wanmin Liu, Peijun Wang

“…Compared with the two models aforementioned, the Radiology MLP model demonstrated a 33.4%-131.3% improvement in NRI and a 9.3%-50% improvement in IDI, showing better discrimination, calibration and clinical usefulness in three sets, which was selected as the optimal predictive model. Conclusion We mainly developed a fusion model (Radiology MLP model) that integrated radiology and radiomics features using MLP deep learning algorithm to predict vessels encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC) patients, which yield an incremental value over the radiology and the MLP model.…”
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An automated network-based tool to search for metabolic vulnerabilities in cancer by Luis V. Valcárcel, Edurne San José-Enériz, Raquel Ordoñez, Iñigo Apaolaza, Danel Olaverri-Mendizabal, Naroa Barrena, Ana Valcárcel, Leire Garate, Jesús San Miguel, Antonio Pineda-Lucena, Xabier Agirre, Felipe Prósper, Francisco J. Planes

“…Here, we present gmctool, a freely accessible online tool that allows us to accomplish this task in a simple, efficient and intuitive environment. gmctool exploits the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to synthetic lethality based on genome-scale metabolic networks, including a unique database of synthetic lethals computed from Human1, the most recent metabolic reconstruction of human cells. gmctool introduces qualitative and quantitative improvements over our previously developed algorithms to predict, visualize and analyze metabolic vulnerabilities in cancer, demonstrating a superior performance than competing algorithms. …”
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Machine learning based calculation of refractive index of polyethylene glycol polymer by Walid Abdelfattah, Munthar Kadhim Abosaoda, Hardik Doshi, H.S. Shreenidhi, Manoranjan Parhi, Devendra Singh, Prabhjot Singh, Bilakshan Purohit, Kamal Kant Joshi, Ahmad Abumalek

“…This study develops advanced machine learning algorithms to accurately predict the refractive index of polyethylene glycol (PEG) polymers using temperature and molecular weight as key input variables. …”
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Quality of life and physical working capacity in pulmonary sarcoidosis by A. L. Gudim, L. B. Postnikova, V. A. Kostrov, A. A. Mironov, N. I. Kubysheva

“…In patients with low QOL, CPET can be used to determine the PWC and mechanisms of its reduction. The presented diagnostic algorithm will optimize the choice of therapy for patients with sarcoidosis.…”
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Advanced control parameter optimization in DC motors and liquid level systems by Serdar Ekinci, Davut Izci, Mohammad H. Almomani, Kashif Saleem, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu, Laith Abualigah

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Comprehensive Analysis of the Role of Metabolic Features in Osteoporosis: A Multi-Omics Analysis by Chang S, Tao W, Shi P, Wu H, Liu H, Xu J, Chen J, Zhu J

“…Additionally, 13 differentially expressed TFs were predicted to regulate the expression levels of these 23 miRNAs. …”
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Forecasting Stock Market Volatility Using Housing Market Indicators: A Reinforcement Learning-Based Feature Selection Approach by Pourya Zareeihemat, Samira Mohamadi, Jamal Valipour, Seyed Vahid Moravvej

“…This study tackles the complex challenge of accurately predicting stock market volatility through indicators from the housing market. …”
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Wound imaging software and digital platform to assist review of surgical wounds using patient smartphones: The development and evaluation of artificial intelligence (WISDOM AI stud... by Melissa Rochon, Judith Tanner, James Jurkiewicz, Jacqueline Beckhelling, Akuha Aondoakaa, Keith Wilson, Luxmi Dhoonmoon, Max Underwood, Lara Mason, Roy Harris, Karen Cariaga

“…Secondary objectives focused on specificity, positive predictive value (PPV), and negative predictive value (NPV) for various wound features.…”
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Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. The AL algorithm enhances the ANN model’s predictive ability, resulting in a 57.9% decrease in operating costs and a 0.010682 loss of energy supply probability (LESP) value. …”
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RESULTS OF USTEKINUMAB TREATMENT IN PATIENTS WITH PSORIATIC ARTHRITIS IN THE RUSSIAN FEDERATION ACCORDING TO THE DATA OF PSUMMIT 1 AND PSUMMIT 2 by Yu. L. Korsakova, A. A. Godzenko, A. O. Pchelintseva, O. Yu. Grigoryeva, L. N. Denisov, E. L. Nasonov

“…After 16 weeks the patients showing a less than 5% reduction  in the number of tender and swollen joints were given UST 45 mg (if they belonged to the PL group) or 90 mg (if they were in the UST 45-mg group). …”
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Machine Learning‐Enhanced Optimization for High‐Throughput Precision in Cellular Droplet Bioprinting by Jaemyung Shin, Ryan Kang, Kinam Hyun, Zhangkang Li, Hitendra Kumar, Kangsoo Kim, Simon S. Park, Keekyoung Kim

“…., bioink viscosity, nozzle size, printing time, printing pressure, and cell concentration), and develop algorithms capable of immediate cellular droplet size prediction. …”
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Autoconcepto físico en estudiantes universitarios: Generación de perfiles por clasificación jerárquica sobre componentes principales (Physical self-concept in university students:... by Luis Alberto Cardozo, Jhonatan C. Peña-Ibagón, Widad Florez-Escobar, Carlos A. Castillo-Daza, Diego A. Bonilla-Ocampo, Javier L. Reina-Monroy

“…The aims of this study were i) to analyze and compare the physical self-concept in university students considering possible differences between sexes and associations with socioeconomic status and age, and ii) to generate student profiles using unsupervised machine learning algorithms. A total of 230 Colombian students between 18 and 38 years of age from the Physical Education (n = 118) and Psychology (n = 112) majors participated in this cross-sectional study. …”
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MATHCAD APPLICATION FOR THE MULTIDIMENSIONAL ANALYSIS OF THE INTERDEPENDENCES ON WORLD STOCK MARKETS by Marina A. Skorik, Andrey G. Nefedov

“…Its usage in the educational process allows to develop stable skills in applying of mathematical and statistical methods of data analysis.…”
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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…ObjectiveThis research aims to leverage the advances of computer algorithms to provide scientific analytical methods for spatial simulation and offer a more objective approach to reflect the natural operational laws of interdependencies between elements in the real physical world for landscape design. …”
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Enhanced estimation of reference evapotranspiration using hybrid deep learning models and remote sensing variables by Tze Ying Fong, Yuk Feng Huang, Ren Jie Chin, Chai Hoon Koo

“…They managed to improve the accuracy of the prediction in most of the cases, with the highest R2 = 0.805 and the lowest prediction errors, MAE = 0.265 mm/day, RMSE = 0.343 mm/day and NRMSE = 0.096. …”
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Enhanced framework for credit card fraud detection using robust feature selection and a stacking ensemble model approach by Rahul Kumar Gupta, Asmaul Hassan, Samir Kumar Majhi, Nikhat Parveen, Abu Taha Zamani, Raju Anitha, Binayak Ojha, Abhinav Kumar Singh, Debendra Muduli

“…The particle swarm optimization (PSO) algorithm is employed to optimize ELM parameters, enhancing generalization and model convergence. …”
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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

“…The adaptive reduction step size is used to replace the reduction step size setting of the original algorithm, which overcomes the shortcomings of low accuracy and poor generalization ability of the existing regression decision tree model. …”
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COMPLEXITY EVALUATION IN THE PROJECTS INVOLVING MOBILE HETEROGENEOUS OBJECTS by A. I. Kuzmich, S. C. Mochulsky, A. N. Valvachev

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On constraint qualifications in mathematical programming by L. I. Minchenko, S. I. Sirotko

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