Clinical and pharmacological monitoring of drug safety in pediatrics by N. V. Verlan, E. O. Kochkina, A. V. Kochkin, L. V. Okhremchuk, A. V. Popadyuk

“…Introduction of monitoring methods and prediction algorithms allowing to reveal with high probability and to prevent adverse drug reactions in children improved efficiency and quality of pharmacotherapy…”
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Predictors of evacuation behavior: dataset on respondents’ route choice and web interaction by Dajana Snopková, Martin Tancoš, Lukáš Herman, Vojtěch Juřík

“…It supports the development of models to predict human behavior in emergencies using machine learning and predictive modeling and is accessible for both academic and commercial use.…”
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The PLSR-ML fusion strategy for high-accuracy leaf potassium inversion in karst region of Southwest China by Zhihao Song, Zhihao Song, Wen He, Yuefeng Yao, Ling Yu, Jinjun Huang, Yong Xu, Haoyu Wang

“…Validation coefficient of determination (R²) values reached 0.89, 0.94, and 0.96, respectively—representing improvements of 206%, 147%, and 108% over standalone algorithms. This performance gain was attributed to rigorous overfitting control: PLSR’s dimensionality reduction synergized with ensemble machine learning (RF, XGBoost, MLP) to eliminate redundant spectral features while retaining predictive signals. …”
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Physics-informed deep learning model for line-integral diagnostics across fusion devices by Cong Wang, Weizhe Yang, Haiping Wang, Renjie Yang, Jing Li, Zhijun Wang, Yixiong Wei, Xianli Huang, Chenshu Hu, Zhaoyang Liu, Xinyao Yu, Changqing Zou, Zhifeng Zhao

“…The incorporation of the PILF has been shown to correct the model’s predictions, bringing the back-projections closer to the actual inputs and reducing the errors associated with inversion algorithms. …”
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Comparing the effect of pre-anesthesia clonidine and tranexamic acid on intraoperative bleeding volume in rhinoplasty: a machine learning approach by Zahra Asghari Varzaneh, Akram Hemmatipour, Hadi Kazemi-Arpanahi

“…The findings were then compared to determine the most effective medication and the best predictive model. The results revealed that the Linear and Ridge regression algorithms outperformed all other models based on three evaluation metrics: mean absolute error (MAE), mean square error (MSE), and R-squared. …”
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Development and Implementation of a Machine Learning‐Based Flood Forecasting System in Kasese District, Uganda by Edward Miiro, Ismael Kato, Zuhra Nantege, Samuel Ssendi, Khasim Bassajjalaba

“…Two machine learning algorithms, including linear regression and K‐nearest neighbours (KNN) were used to learn from collected hydrological data and make necessary predictions. …”
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Diagnostic Models for Differentiating COVID-19-Related Acute Ischemic Stroke Using Machine Learning Methods by Eylem Gul Ates, Gokcen Coban, Jale Karakaya

“…<b>Results:</b> This study assessed the performance of dimensionality reduction and classification algorithms in distinguishing COVID-19-negative and COVID-19-positive cases using radiomics data from brain MR scans. …”
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Efficacy of drugs most commonly prescribed at functional gastrointestinal diseases (functional dyspepsia syndrome and irritable bowel syndrome) observational study results by V. T. Ivashkin, Ye. A. Poluektova, D. V. Reykhart, O. S. Shifrin, A. G. Beniashvili, O. S. Lyashenko, A. V. Belostotsky

“…It is established that presence of probiotic in the treatment mode leads to significant reduction in main symptoms severity typical both for FD and IBS according to the «7×7» questionnaire.…”
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Differentiation of Organic Cocoa Beans and Conventional Ones by Using Handheld NIR Spectroscopy and Multivariate Classification Techniques by Elliot K. Anyidoho, Ernest Teye, Robert Agbemafle

“…Second derivative preprocessing together with PLS-DA algorithm was superior to the rest of the algorithms with a classification accuracy of 100.00% in both the calibration set and prediction set. …”
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Enhancing Performance and Stability of Wing-Alone UAV: A Comprehensive Mathematical Model and Simulation Approach Using MATLAB and Simulink by G. Ramanan, N. Rahul, V. E. Sathishkumar, Indraraj Upadhyaya

“…The novel objective of this study is enhancing the performance and stability aspects of the wing-alone UAV through code-based reports and the implementation of custom MATLAB algorithms. The wing-alone UAV demonstrated a 15% improvement in aerodynamic efficiency and a 10% reduction in overall weight compared to baseline designs. …”
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An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system by Bishwajit Dey, Gulshan Sharma, Pitshou N. Bokoro, Soham Dutta

“…Abstract The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. …”
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A machine learning approach to assess the climate change impacts on single and dual-axis tracking photovoltaic systems by Udit Mamodiya, Indra Kishor, Priyam Ganguly, Isha Mukherjee, Nithesh Naik

“…This paper introduces COMLAT (Climate-Optimized Machine Learning Adaptive Tracking), an AI solar tracking system that employs climate prediction using CNN-LSTM for climate prediction, XGBoost for estimation of energy yield, and Deep Q-Learning (DQL) for real-time tracking control for solar efficiency optimization. …”
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Integrating artificial intelligence into thermodynamics: A new paradigm for sustainable future by Marwan Al-Raeei

“…By integrating machine learning algorithms and statistical techniques into predictive modeling, we demonstrate that it is possible to develop highly accurate models that forecast performance based on historical data. …”
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AI-powered Somatic Cancer Cell Analysis for Early Detection of Metastasis: The 62 principal Cancer Types by Sandile Buthelezi, Solly Matshonisa Seeletse, Taurai Hungwe, Vimbai Mbirimi-Hungwe

“…Furthermore, the models demonstrated exceptional predictive accuracy, with XGBoost and Support Vector Machines achieving an accuracy of 0.95. …”
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Leveraging the Power of Deep Learning Technique for Creating an Intelligent, Context-Aware, and Adaptive M-Learning Model by Muhammad Adnan, Duaa H. AlSaeed, Heyam H. Al-Baity, Abdur Rehman

“…Particularly, in educational institutions, ML and DL algorithms can help instructors in predicting the learning performance of learners. …”
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An efficient real-time signal processing method for satellite laser ranging. by Jinyu Wang, Wei Zhu, Weiming Gong

“…To address these problems, we propose a new, efficient real-time SLR data processing method. This algorithm combines single-stage filtering with a histogram-based approach and incorporates polynomial fitting to establish a predictive model. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…A total 15 methods/algorithms were evaluated against prediction accuracy across 20 RSSI datasets, incorporating diverse hall cell allocations and visitor movement patterns. …”
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Methods of Thermal Calculations for a Condensing Waste-Heat Exchanger by Rączka Paweł, Wójs Kazimierz

“…Thanks to this, it was possible to calculate more accurately the required heat transfer area, which resulted in its reduction by 19 %. In addition, the influence of the mass transfer on the heat transfer area was taken into account, which contributed to a further reduction in the calculated size of the heat exchanger - in total by 28% as compared with the Colburn-Hobler algorithm. …”
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Integrating holographic counterparts for intelligent IoT consumer devices by M. Rajesh, M. Usha, Sathishkumar Veerappampalayam Easwaramoorthy

“…Advancements in quantum algorithms for predictive learning, self-optimization through more integrated machine learning models, and the development of standardised interoperability protocols to facilitate wider industrial usage are all areas that will be investigated in future research.…”
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miRTARGET: An integrated web tool for the identification of microRNA targets with potential therapeutic or prognostic value in cancer by Matjaz Rokavec, Heiko Hermeking

“…It integrates experimental miRNA-related datasets and computational algorithms to generate prediction scores for targets of 1744 human miRNAs. …”
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