Neural Networks in Forecasting Disease Dynamics by A. G. Hasanov, D. G. Shaybakov, S. V. Zhernakov, A. M. Men’shikov, F. F. Badretdinova, I. F. Sufiyarov, J. R. Sagadatova

“…The best convergence of the network learning process is provided by the quasi-Newton and conjugated gradient algorithms. In order to assess the effectiveness of the proposed neural network in predicting the dynamics of inflammation, a comparative analysis was carried out using a number of conventional methods, such as exponential smoothing, moving average, least squares and group data handling.Conclusion.The proposed neural network based on approximation and extrapolation of variations in the patient’s medi‑ cal history over fixed time window segments (within the ‘sliding time window’) can be successfully used for forecasting the development and outcome of erysipelas.…”
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Healthcare Economics-Vital Threat Detection System Efficiency: A Business Process Analysis Methodology by Salma Elhag, Amal Alghamdi, Amal Alahmari, Abeer Alharbi

“…The data is sent to the cloud, where it is stored and analyzed using artificial intelligence (AI) algorithms to predict critical health conditions. When any abnormalities are detected, immediate alerts are sent to family members or caregivers via mobile applications, enabling a quick response. …”
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Estimating Aggregate Capacity of Connected DERs and Forecasting Feeder Power Flow With Limited Data Availability by Amir Reza Nikzad, Amr Adel Mohamed, Bala Venkatesh, John Penaranda

“…The method is tested using a North American utility feeder data, achieving an average accuracy of 95.56% for forecasting aggregate load power, 93.70% for feeder flow predictions, and 97.53% for estimating the aggregate capacity of DERs.…”
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Analysis of State-of-Charge Estimation Methods for Li-Ion Batteries Considering Wide Temperature Range by Yu Miao, Yang Gao, Xinyue Liu, Yuan Liang, Lin Liu

“…Accurate state-of-charge (SOC) estimation is critical for optimizing battery performance, ensuring safety, and predicting battery lifetime. However, SOC estimation faces significant challenges under extreme temperatures and complex operating conditions. …”
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Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data by Pierfranco Costabile, Carmelina Costanzo, John Kalogiros, Vasilis Bellos

“…Abstract In our era, the rapid increase of parallel programming coupled with high‐performance computing (HPC) facilities allows for the use of two‐dimensional shallow water equation (2D‐SWE) algorithms for simulating floods at the “hydrological” catchment scale, rather than just at the “hydraulic” fluvial scale. …”
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A survey on exploring the challenges and applications of wireless body area networks (WBANs) by Arun Sekar Rajasekaran, L. Sowmiya, Azees Maria, R. Kannadasan

“…Due to the arrival of the Micro Electromechanical System (MEMS) and several intelligent sensors, collaboration with WBAN makes accurate predictions of parameters in the human body. WBAN has numerous applications in medical and non-medical fields. …”
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Improving thyroid disorder diagnosis via innovative stacking ensemble learning model by Ayesha Hassan, Shabana Ramzan, Ali Raza, Muhammad Munwar Iqbal, Aseel Smerat, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

“…Five advanced machine learning (ML) algorithms, logistic regression, support vector machine, decision tree, random forest, and gradient boosting are employed to develop predictive models. …”
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The role of hematological parameters as predictors of mortality in elderly patients in the hospital period by L. V. Borisova, S. A. Rukavishnikova, A. S. Pushkin, T. A. Ahmedov, V. V. Yakovlev

“…The development of algorithms for predicting adverse outcomes, including death in elderly and senile patients, is an urgent issue. …”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…Global models, such as flux balance analysis (FBA), integrate genome-scale networks to predict cellular behavior and optimize production conditions. …”
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FEATURES OF THE TREATMENT OF HYPERMOBILITY OF THE ARTICULAR HEADS AND DISLOCATIONS OF THE LOWER JAW ON THE BACKGROUND OF FRACTURES OF THE CONDYGAL PROCESSES OF THE MANDIBLE, AS A P... by O.A. Toropov, D.S. Avetikov, M.G. Skikevych, O.S. Ivanytska, O.O. Rozkolupa, K.P. Lokes

“…The analysis of clinical case data allows us to state that the goal of treatment should be to return the condyles to their original physiological position, and conservative methods should be in the first place when creating an algorithm. Early manual reduction of the joint heads is the best method of treatment, if it is possible to carry it out in a timely manner. …”
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Determination of Colles fracture risk index by X-ray images with the computer vision application by Wisam A. Hussein, Hussain J. AlKhatteib, Jawad K. Abbas

“…Background. Modelling a predictive risk index for Colles fractures using X-ray image analysis is a crucial application in orthopaedics since these fractures have essential health and economic burdens, particularly among the elderly. …”
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Survival analysis using machine learning in transplantation: a practical introduction by Andrea Garcia-Lopez, Maritza Jiménez-Gómez, Andrea Gomez-Montero, Juan Camilo Gonzalez-Sierra, Santiago Cabas, Fernando Giron-Luque

“…The integration of machine learning techniques, particularly the Random Survival Forest (RSF) model, offers potential enhancements to predictive modeling and decision-making. This study aims to provide an introduction to the application of the RSF model in survival analysis in kidney transplantation alongside a practical guide to develop and evaluate predictive algorithms. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…The Gradient Boosting algorithm achieved the best performance with a predictive R2 of 0.87 and an RMSE of 0.537 in test set. …”
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Diagnostic value of leukocytosis in patients presenting to the emergency department with abdominal pain: A retrospective observational study by Erkan Boğa

“…Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of leukocytosis in predicting surgical needs were calculated. …”
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SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

“…By incorporating soft labels and soft central region loss, our model is guided to prioritize high-quality, well-aligned predictions. We evaluate SCoralDet on the Soft-Coral dataset, achieving an inference latency of 9.52 ms and an mAP50 of 81.9. …”
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Effective tweets classification for disaster crisis based on ensemble of classifiers by Christopher Ifeanyi Eke, Kholoud Maswadi, Musa Phiri, Mulenga, Mohammad Imran, Dekera Kwaghtyo, Akeremale Olusola Collins

“…The proposed approach demonstrates not only high predictive capacity but also scalability for real-time tweet filtering during emergencies. …”
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Imaging genomics of cancer: a bibliometric analysis and review by Xinyi Gou, Aobo Feng, Caizhen Feng, Jin Cheng, Nan Hong

“…It has been widely applied to explore heterogeneity and predict responsiveness and disease progression in cancer. …”
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Clinical Utility of Bladder Cancer Biomarkers by Laura Maria Krabbe, Georgios Gakis, Yair Lotan

“…The need for frequent follow-up, including invasive procedures like cystoscopy, repetitive procedures like transurethral resection of bladder tumors and intravesical instillation therapy in non-muscle invasive stages, as well as systemic treatment with or without radical local treatment in advanced stages, makes bladder cancer one of the most expensive cancers to treat. Prognostic and predictive biomarkers have the potential to fundamentally change bladder cancer treatment algorithms, which may result in improved patient comfort and oncological outcomes and may also decrease the socioeconomic burden of the disease. …”
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High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”
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Advanced Soft Computing Ensemble for Modeling Contaminant Transport in River Systems: A Comparative Analysis and Ecological Impact Assessment by Jafar Chabokpour

“…The research employed various techniques, including Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Support Vector Regression (SVR), and Genetic Algorithms (GA), to predict pollutant concentrations and estimate transport parameters. …”
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