Artificial intelligence in teaching programming to students of pedagogical university by I. A. Yashina

“…The purpose of the study. Modern education is undergoing significant changes. Artificial intelligence technologies are being introduced into the educational practice of universities, including pedagogical universities. …”
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Sensitization peculiarities for children with allergic rhinitis living in Magnitogorsk and Beloretsk cities by E. V. Andronova, T. S. Lepeshkova

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Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography by Ramyashree, P. S. Venugopala, S. Raghavendra, Vijay S. Kubihal

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Network characteristics of comorbid symptoms in alcohol use disorder by Xin Yu, Wen Zhang, Can Wang, Guolin Mi, Xiuzhe Chen, Yanhu Wang, Xu Chen

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Personalized dosing protocol for extended-release tacrolimus in kidney transplant recipients in the early postoperative period by A. V. Shabunin, P. A. Drozdov, D. A. Makeev, I. V. Nesterenko, O. S. Zhuravel, L. R. Karapetyan, S. A. Astapovich, Е. A. Lidzhieva

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Consensus Guidelines of Russian Society of Radiology (RSR) and Russian Association of Specialists in Ultrasound Diagnostics in Medicine (RASUDM) «Role of Imaging (X-ray, CT and US)... by V. E. Sinitsyn, I. E. Tyurin, V. V. Mitkov

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Interpretable multiparametric MRI radiomics-based machine learning model for preoperative differentiation between benign and malignant prostate masses: a diagnostic, multicenter st... by Wenjun Zhou, Wenjun Zhou, Zhangcheng Liu, Zhangcheng Liu, Jindong Zhang, Shuai Su, Yu Luo, Lincen Jiang, Kun Han, Guohua Huang, Jue Wang, Jianhua Lan, Delin Wang

“…SHAP can disclose the underlying prediction process of the ML model, which may promote its clinical applications.…”
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Molecular characterization and prognostic modeling associated with M2-like tumor-associated macrophages in breast cancer: revealing the immunosuppressive role of DLG3 by Ziqiang Wang, Jing Zhang, Huili Chen, Xinyu Zhang, Kai Zhang, Feiyue Zhang, Yiluo Xie, Hongyu Ma, Linfeng Pan, Qiang Zhang, Min Lu, Hongtao Wang, Chaoqun Lian

“…Consensus clustering analysis identified three molecular subtypes with distinct clinical features, and we explored potential differences in genomic mutations, pathway enrichment, and immune infiltration in patients between subtypes. Machine learning algorithms were used to screen key genes and construct M2-like macrophage-associated prognostic models. …”
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Laser-Induced Breakdown Spectroscopy Quantitative Analysis Using a Bayesian Optimization-Based Tunable Softplus Backpropagation Neural Network by Xuesen Xu, Shijia Luo, Xuchen Zhang, Weiming Xu, Rong Shu, Jianyu Wang, Xiangfeng Liu, Ping Li, Changheng Li, Luning Li

“…Hence chemometrics based on artificial neural network (ANN) algorithms have become increasingly popular in LIBS analysis due to their extraordinary ability in nonlinear feature modeling. …”
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人工智能融合临床与多组学数据在卒中防治及医药研发中的应用与挑战Applications and Challenges of Integrating Artificial Intelligence with Clinical and Multi-omics Data in Stroke Prevention, Treatment, and Pharmaceut... by 勾岚，姜明慧，姜勇，廖晓凌，李昊，张杰，程丝 (GOU Lan, JIANG Minghui, JIANG Yong, LIAO Xiaoling, LI Hao, ZHANG Jie, CHENG Si)

“…By integrating and analyzing clinical and multi-omics data, AI technology enhances the identification of high-risk populations, optimizes early diagnosis and risk assessment, enables precise subtyping of stroke, facilitates the screening of potential drug targets, and constructs prognostic prediction models. However, critical challenges, such as insufficient multi-omics resources, difficulties in multi modal data integration, and limited interpretability of algorithms, remain major bottlenecks in clinical translation. …”
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Pre-treatment tumour PET metrics and clinical outcomes of anal cancer in patients living with and without HIV by Michael Pennock, N. Patrik Brodin, Christian Velten, Megi Gjini, Nitin Ohri, Chandan Guha, Shalom Kalnicki, Wolfgang A. Tome, Madhur K. Garg, Rafi Kabarriti

“…Pre-treatment PET metrics were validated as significantly predicting outcomes for the entire cohort and HIV-negative patients, not PLWH. …”
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Forestry climate adaptation with HarvesterSeasons service—a gradient boosting model to forecast soil water index SWI from a comprehensive set of predictors in Destination Earth by Mikko Strahlendorff, Anni Kröger, Golda Prakasam, Miriam Kosmale, Mikko Moisander, Heikki Ovaskainen, Asko Poikela

“…The Copernicus Global Land Monitoring Service’s Soil Water Index (SWI) satellite-based observations from 2015 to 2023 at 10,000 locations in Europe were used as the predictand (target parameter) to train an artificial intelligence (AI) model to predict soil wetness with XGBoost (eXtreme Gradient Boosting) and LightGBM (Light Gradient Boosting Machine) implementations of gradient boosting algorithms. …”
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Machine learning applications in forecasting patient satisfaction and clinical outcomes after carpal tunnel release: a retrospective study by Zohreh Manoochehri, Sara Manoochehri, Seyed Reza Bagheri, Alireza Abdi, Ehsan Alimohammadi

“…Four machine learning algorithms—random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), and k-nearest neighbors (k-NN)—were used to predict these outcomes. …”
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Human responses to the DNA prime/chimpanzee adenovirus (ChAd63) boost vaccine identify CSP, AMA1 and TRAP MHC Class I-restricted epitopes. by Harini Ganeshan, Jun Huang, Maria Belmonte, Arnel Belmonte, Sandra Inoue, Rachel Velasco, Santina Maiolatesi, Keith Limbach, Noelle Patterson, Marvin J Sklar, Lorraine Soisson, Judith E Epstein, Kimberly A Edgel, Bjoern Peters, Michael R Hollingdale, Eileen Villasante, Christopher A Duplessis, Martha Sedegah

“…Individual antigen-specific 15mers in the subpools with strong responses were then deconvoluted, evaluated for activities, and MHC Class I-restricted epitopes within the active 15mers were predicted using NetMHCpan algorithms. The predicted epitopes were synthesized and evaluated in the FluoroSpot IFN-γ and GzB assays.…”
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An Upscaling-Based Strategy to Improve the Ephemeral Gully Mapping Accuracy by Solmaz Fathololoumi, Daniel D. Saurette, Harnoordeep Singh Mann, Naoya Kadota, Hiteshkumar B. Vasava, Mojtaba Naeimi, Prasad Daggupati, Asim Biswas

“…Employing the Random Forest (RF) algorithm, this study executed three distinct strategies for EGs identification. …”
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Analytical Study of Fractional-Order Multiple Chaotic FitzHugh-Nagumo Neurons Model Using Multistep Generalized Differential Transform Method by Shaher Momani, Asad Freihat, Mohammed AL-Smadi

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TSHD: Topic Segmentation Based on Headings Detection (Case Study: Resumes) by Majd E. Tannous, Wassim H. Ramadan, Mohanad A. Rajab

“…We apply the algorithm to extract resume segments and identify their topics. …”
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Development and validation of a nomogram for differentiating immune checkpoint inhibitor-related pneumonitis from pneumonia in patients undergoing immunochemotherapy: a multicenter... by Linli Duan, Guanglu Liu, Zijie Huang, Rong Chen, Di Mo, Yuxiao Xia, Jiazhu Hu, Mengzhang He

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Study of the interval width of features for improving forecasting efficiency of the transport flow intensity by I. N. Pugachev, N. G. Sheshera, D. Yе. Grigorov

“…There are a lot of methods for increasing the accuracy of predictive models, but this method has been used for the first time. …”
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Identification and validation of integrated stress-response-related genes as biomarkers for age-related macular degeneration by Jingyi Niu, Ling Jin, Yijun Hu, Yiting Wang, Xiaoning Hao, Wenwen Geng, Ruirui Ma

“…We obtained thirteen relevant miRNAs and 27 TFs by prediction, with three shared TFs, and seventeen potentially effective drugs were predicted. …”
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