Principles of physical factor selection in the early postoperative period of breast cancer treatment: a randomized controlled study by Inna S. Evstigneeva

“…INTRODUCTION. Current models of onco-rehabilitation do not consider the patient’s functional impairment during combined treatment until the patient becomes incapacitated and the impairment develops into a chronic condition. …”
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Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS) by Ray L. Khuboni, Hongjun Xu

“…Multiple view stereopsis (MVS) algorithms have achieved substantial advancements in 3D reconstruction accuracy and completeness. …”
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Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool by Hatem Ali, Arun Shroff, Tibor Fülöp, Miklos Z. Molnar, Adnan Sharif, Bernard Burke, Sunil Shroff, David Briggs, Nithya Krishnan

“…However, the discriminative or calibration capacity of the currently employed models are limited. We set out to apply artificial intelligence (AI) algorithms to create a highly predictive risk stratification indicator, applicable to the UK’s transplant selection process.Methodology: Pre-transplant characteristics from 12,661 live-donor kidney transplants (performed between 2007 and 2022) from the United Kingdom Transplant Registry database were analyzed. …”
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MODERN APPROACHES AND TECHNOLOGIES OF PSYCHOLOGICAL SUPPORT OF FAMILIES OF PARTICIPANTS (VETERANS) OF A SPECIAL MILITARY OPERATION by Roza I. Kadieva, Aizanat R. Davudova

“…Modeling — development of psychological support technologies based on the collected data, taking into account the specifics of working with children and families of military personnel. …”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…Abstract Hearing loss poses immense burden worldwide and early detection is crucial. The accurate models identify high-risk groups, enabling timely intervention to improve quality of life. …”
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Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review by Ashish Aggarwal, Akanksha Mishra, Nazia Tabassum, Young-Mog Kim, Fazlurrahman Khan

“…The new approach demonstrated that a variety of AI technologies could be correlated. Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. …”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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Spatial pattern and heterogeneity of green view index in mountainous cities: a case study of Yuzhong district, Chongqing, China by Aiping Gou, Xuyuan Wang, Jiangbo Wang, Chenjie Wang, Guanzheng Tan

“…The results indicate that: (1) In Yuzhong District, 58.9% of streets have a GVI within a low to moderate range, suggesting room for improvement. Higher GVI levels are generally associated with elevated Digital Elevation Models (DEM), while slope, aspect, and terrain undulation have relatively minor overall impacts on GVI. (2) The GVI is highest in the western regions and lowest in the eastern regions, with streets along the riversides exhibiting lower GVI levels. (3) GWR analysis reveals that road type and NDVI significantly influence the GVI. …”
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Automatic screening for posttraumatic stress disorder in early adolescents following the Ya’an earthquake using text mining techniques by Yuzhuo Yuan, Yuzhuo Yuan, Zhiyuan Liu, Wei Miao, Xuetao Tian

“…Meanwhile, participants completed the PTSD Checklist for DSM-5 (PCL-5). Text classification models were constructed using three supervised learning algorithms (BERT, SVM, and KNN) to identify PTSD symptoms and their corresponding behavioral indicators in each sentence of the self-narratives.ResultsThe prediction accuracy for symptom-level classification reached 73.2%, and 67.2% for behavioral indicator classification, with the BERT performing the best.ConclusionsThese findings demonstrate that self-narratives combined with text mining techniques provide a promising approach for automated, rapid, and accurate PTSD screening. …”
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Predicting Court Judgment in Criminal Cases by Text Mining Techniques by Mohammad Farhadishad, Mohammad Kazemifard, Zahra Rezaei

“…Legal judgment prediction with artificial intelligence algorithms can benefit judicial bodies, legal experts, and litigants as well as judges. …”
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Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches by Guohua Li, Qian Shi, Qibiao Wu, Xinbing Sui

“…AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. …”
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Transformative applications in biology education: A case study on the efficacy of adaptive learning with numerical insights by Shin I. Aleksandrovich, Tyan Ramazan, Raissa Utegaliyeva, Balzat Sarimbayeva, Gaukhar Keubassova, Rakhima Bissalyyeva, Kuanysh Syman, Gaukhar Abdikarimova

“…Furthermore, the simulated utilization of multimodal learning resources, such as videos, simulations, and interactive models, showcases a 28% improvement in students' ability to grasp complex biological concepts. …”
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Multi-source 3D point clouds fusion for potential rock mass hazard evaluation in high-steep rock slopes by W. Yuan, C. Liu, C. Liu, T. Wang, B. Adriano, H. Bao, R. Shibasaki, S. Koshimura

“…The results demonstrate that the fusion of TLS-UAV multi-source data enhances spatial coverage and point cloud density by 19%, enabling comprehensive slope modeling and improving multi-angle structural characterization of target rock masses. …”
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Nephrotoxicity Biomarkers: Role and Significance in the Diagnosis of Drug-Induced Kidney Injury by O. V. Muslimova, V. A. Evteev, I. A. Mazerkina, E. A. Sokova, A. B. Prokofiev, A. V. Shapchenko, T. V. Alexandrova

“…Thus, further research is necessary to investigate different AKI biomarkers and improve experimental models (both in vivo and in vitro), which will support assessment of potential nephrotoxic properties of existing and new medicinal products.…”
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Graph Split Federated Learning for Distributed Large-Scale AIoT in Smart Cities by Hanyue Xu, Kah Phooi Seng, Li-Minn Ang, Wei Wang, Jeremy Smith

“…A key element of this transformation is the widespread deployment of IoT devices for data collection, which feeds into machine learning algorithms to improve city services. However, the centralization of sensitive IoT data for ML raises privacy and efficiency concerns. …”
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Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review by Émile Lemoine, Joel Neves Briard, Bastien Rioux, Oumayma Gharbi, Renata Podbielski, Bénédicte Nauche, Denahin Toffa, Mark Keezer, Frédéric Lesage, Dang K. Nguyen, Elie Bou Assi

“…Significance: We provide guidelines regarding patient selection, reference standard, algorithms, and performance validation.…”
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Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies by Rahul Kumar, Ethan Waisberg, Joshua Ong, Phani Paladugu, Dylan Amiri, Jeremy Saintyl, Jahnavi Yelamanchi, Robert Nahouraii, Ram Jagadeesan, Alireza Tavakkoli

“…Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. …”
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Anomaly detection with grid sentinel framework for electric vehicle charging stations in a smart grid environment by V. Thiruppathy Kesavan, Md. Jakir Hossen, R. Gopi, Emerson Raja Joseph

“…This technology can also detect and respond to suspicious movements dynamically using powerful machine learning algorithms (long short-term memory (LSTM), random forest, and autoencoder models), ensuring safety. …”
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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

“…Following that, machine learning (ML) models are constructed based on the prominent pro-groups, which enable the extraction of promising biomarkers for distinguishing BRCA sub-types. …”
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An engineering practical three-dimensional sliding cable element by Binlin Xu, Gen He, Fanbo Guo

“…Abstract Aiming at the difficulty of accurately modeling the friction slip effect in engineering calculations for multi-span continuous cable structures, it is proposed to develop a three-dimensional slip cable element USER101 by using the secondary development platform of ANSYS-UPFs combined with the catenary theory and the Euler-Eytelwein formula. …”
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