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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Digital health technologies in Kurdistan region of Iraq: a narrative review of enhancing healthcare accessibility and quality by Zhinya Kawa Othman, Shuaibu Saidu Musa, Mohamed Mustaf Ahmed, Olalekan John Okesanya, Omar Abdulkarim Saeed Alhammadi, Don Lucero-Prisno Eliseo

“…This review describes several digital health technologies in Kurdistan, including software implementation for data management, such as District Health Information Software 2, the establishment of telemedicine services, and the utilization of machine learning algorithms for mortality prediction, particularly during the COVID-19 pandemic. …”
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State-Dependent Transcranial Magnetic Stimulation Synchronized with Electroencephalography: Mechanisms, Applications, and Future Directions by He Chen, Tao Liu, Yinglu Song, Zhaohuan Ding, Xiaoli Li

“…Future directions emphasize adaptive algorithms for neural state prediction, phase-specific stimulation protocols, and standardized methodologies to enhance reproducibility. …”
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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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A Review of Vehicle Dynamics and Control Approaches for Mitigating Motion Sickness in Autonomous Vehicles by Ilhan Yunus, Georgios Papaioannou, Jenny Jerrelind, Lars Drugge

“…Effective mitigation requires accurate and reliable prediction. In this context, motion-based prediction approaches, recognised for their practicality, cost-effectiveness, and promising results, are examined in detail with particular focus on ISO-based methods and sensory conflict theory-based models. …”
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Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling by Sahil Grover, Viveksheel Rajput, Sanjay Kumar Mangal, Sarbjit Singh, Sandeep Singh, Shubham Sharma, Ehab El Sayed Massoud, Dražan Kozak, Jasmina Lozanovic

“…Machine learning-based algorithms are also used to predict the responses using Random Forest and Gradient Boost approaches. …”
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Enhancing PV feed-in power forecasting through federated learning with differential privacy using LSTM and GRU by Pascal Riedel, Kaouther Belkilani, Manfred Reichert, Gerd Heilscher, Reinhold von Schwerin

“…By leveraging advanced FL algorithms such as FedYogi and FedAdam, we propose a method that not only predicts sequential energy data with high accuracy, achieving an R2 of 97.68%, but also adheres to stringent privacy standards, offering a scalable solution for the challenges of smart grids analytics, thus clearly showing that the proposed approach is promising and worth being pursued further.…”
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Simulating fluvial sediment pulses using remote sensing and machine learning: Development of a modeling framework applicable to data rich and scarce regions by Abhinav Sharma, Celso Castro-Bolinaga, Natalie Nelson, Aaron Mittelstet

“…Various combinations of predictor variables, training algorithms including linear regression and additional machine learning methods, and input data availability scenarios were examined to comprehend the factors influencing turbidity prediction on a regional scale. …”
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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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Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

“…Additionally, the study explores key applications of precision fertilization, including data-driven fertilizer recommendations, aerial crop monitoring, real-time nutrient deficiency prediction, automated and optimized fertilization systems, and organic and eco-friendly nutrient management practices. …”
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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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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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Pistachio Classification Based on Acoustic Systems and Machine Learning by Yavuz Türkay, Zekiye Seyma Tamay

“…These features are given as input to a support vector machine algorithm called FITCSVM for classification. FITCSVM is an algorithm that can perform one-class and two-class (binary) classification on low or medium-sized prediction datasets. …”
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Reinforcement learning in artificial intelligence and neurobiology by Tursun Alkam, Andrew H Van Benschoten, Ebrahim Tarshizi

“…In parallel, we discuss how neurobiological findings, especially the role of dopamine in encoding reward prediction errors, have inspired biologically grounded RL models. …”
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Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data by Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac

“…The work opens new directions in learning over complex structures, transcending transformer-based and traditional hypergraph-based algorithms. We validate results through theoretical analysis and real-world experiments, while demonstrating superior performance in, e.g., stock market prediction.…”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…This study presents a novel, hybrid ensemble learning-based intrusion detection framework that integrates deep learning and traditional ML algorithms with explainable artificial intelligence for real-time cybersecurity applications. …”
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Resolving Covid-19 with Blockchain and AI by Suyogita Singh, Satya Bhushan Verma

“…In that review, many potential blockchain applications were discovered; however, the majority of them were still in their infancy, and it couldn’t yet be predicted how they could contribute to the fight against COVID-19 through the use of platforms, access kinds, and consensus algorithms. …”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Improving survival time and predicting prognosis for distinct molecular profiles is substantial. …”
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