Therapy and rehabilitation of women with diabetic adhesive capsulitis by Iryna Zharova, Yevhen Orlenko

“…The objectives of the developed program were: normalization of blood glucose levels, normalization of the functions of damaged limbs, reduction of pain syndrome, restoration of joint mobility, improvement of quality of life. …”
Get full text

TRAINING SYSTEM OF FUTURE SPECIALISTS: QUALITY CONTROL by Vladimir A. Romanov, Valentina N. Kormakova, Elena N. Musaelian

“…The strategy of the development of the process of quality control training in educational professional organizations and a predictive model of the system of quality control training for future engineers and workers have been created on the analysis and synthesis of a quantitative specification of the quality, the obtained experience and success in control training of future specialists in educational professional organizations in recent economic and educational conditions.Scientific novelty. …”
Get full text

Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study by Yejing Zhao, Yejing Zhao, Xiang Wang, Jie Zhang, Yanyan Zhao, Yi Li, Ji Shen, Ying Yuan, Jing Li

“…Therefore, the high expression of plasma FGF2 and YAP1 proteins may be independent predictive risk factors for MCI in the elderly. Our findings may provide targets for the development of early minimally invasive, efficient, and convenient screening tools, and even for the treatment of AD in the future.…”
Get full text

Investigating Spatial Effects through Machine Learning and Leveraging Explainable AI for Child Malnutrition in Pakistan by Xiaoyi Zhang, Muhammad Usman, Ateeq ur Rehman Irshad, Mudassar Rashid, Amira Khattak

“…The use of machine learning algorithms, specifically XGBoost and Random Forest, highlighted the significant role played by the average value in the neighbourhood in predicting childhood stunting in nearby districts, confirming that the spatial spillover effect is not bounded by geographical boundaries. …”
Get full text

Identification of subtypes and biomarkers associated with disulfidptosis-related ferroptosis in ulcerative colitis by Yinghao Jiang, Hongyan Meng, Xin Zhang, Jinguang Yang, Chengxin Sun, Xiaoyan Wang

“…Next, the hub genes were identified by differential analysis and WGCNA algorithms, and three machine learning algorithms were used to screen biomarkers for UC from hub genes. …”
Get full text

AFM Image Segmentation Based on Wave Growth of Local Maximum Regions with their Selection in Order of Decreasing Values by V. V. Rabtsevich, V. Y. Tsviatkou

Get full text

Quantitative Analysis of Structural Parameters Importance of Helical Temperature Microfiber Sensor by Artificial Neural Network by Juan Liu, Minghui Chen, Hang Yu, Jinjin Han, Hongyi Jia, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, Hao Dai

“…The relative output intensities of HMF sensor at different temperatures are predicted by the BPNN with the HMF’s structural parameters as the input variables. …”
Get full text

Classification of SERS spectra for agrochemical detection using a neural network with engineered features by Mateo Frausto-Avila, Monserrat Ochoa-Elias, Jose Pablo Manriquez-Amavizca, María del Carmen González-López, Gonzalo Ramírez-García, Mario Alan Quiroz-Juárez

“…The model demonstrates strong predictive performance, achieving high precision and recall values across all classes, with an overall classification accuracy of 98.5% for organophosphate pesticides and their mixtures. …”
Get full text

Multi-stage Optimization Forecast of Short-term Power Load Based on VMD and PSO-SVR by Wenwu LI, Qiang SHI, Dan LI, Qunyong HU, Yun TANG, Jinchao MEI

“…In the second stage, phase space reconstruction is used to optimize and reorganize each sequence component, and establish support vector regression（SVR）prediction model for each component. In the third stage, the particle swarm optimization（PSO）algorithm is applied to optimize the internal parameters of the SVR model to facilitate better training and forecasting. …”
Get full text

Application of Big Data Technology in the EMU Fault Early Warning by WU Zhenyi

“…It uses a method of combining equipment fault mechanism and artificial intelligence algorithm to construct a fault early warning and prediction model of key components of EMU, which reflects the working status of a component with its key physical properties and identify potential faults in advance. …”
Get full text

CYLD as a key regulator of myocardial infarction-to-heart failure transition revealed by multi-omics integration by Jingya Xu, Jingya Xu, Zhonghua Dong, Zhaodong Li, Xuan Wang, Xuan Wang

“…Single-cell transcriptomic analysis demonstrated that CYLD exhibited the strongest correlation with the transition from MI to HF; using random forest modelling, we validated its predictive value in this context.DiscussionIn conclusion, our study identified CYLD as a critical regulator of the transition from MI to HF. …”
Get full text

Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…This extended dataset enables a more accurate assessment of ageing trends, enhances the reliability of predictive maintenance models, and supports informed decision-making for asset management in legacy power systems.…”
Get full text

Enhancing Real-Time Emotion Recognition in Classroom Environments Using Convolutional Neural Networks: A Step Towards Optical Neural Networks for Advanced Data Processing by Nuphar Avital, Idan Egel, Ido Weinstock, Dror Malka

“…An experimental validation was conducted in a classroom with 45 students, demonstrating that the level of understanding in the class as predicted was 43–62.94%, and the proposed CNN algorithm (facial expressions detection) achieved an impressive 83% accuracy in understanding students’ emotional states. …”
Get full text

Modeling Topic-Specific Influential Users in QA Forums Using Association Rule Mining by Umar Ishfaq, Tassawar Ali, Ali Daud, Mohammed Alreshoodi, Azeem Irshad

“…This paper incorporates association rule mining (ARM) based algorithms, that are mostly used for market-basket analysis, for exploring the behavior of users and predict their participation in social interactions. …”
Get full text

Achieving Closed-Loop Control Simulation of Human-Artefact Interaction: A Comparative Review by Wilhelm Frederik van der Vegte, Imre Horváth

“…For human decision making, however, validated algorithms exist only to predict the timing but not the reasoning behind it. …”
Get full text

Discovery of Meaningful Rules by using DTW based on Cubic Spline Interpolation by Luis Alexander Calvo-Valverde, David Elías Alfaro-Barboza

“…Short-term predictions based on “the shape” of meaningful rules lead to a vast number of applications. …”
Get full text

Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab by Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein

“…Future research should focus on refining AI models to improve predictive accuracy and assessing long-term outcomes to further optimize disease management. …”
Get full text

In Vitro Oral Cavity Permeability Assessment to Enable Simulation of Drug Absorption by Pankaj Dwivedi, Priyata Kalra, Haiying Zhou, Khondoker Alam, Eleftheria Tsakalozou, Manar Al-Ghabeish, Megan Kelchen, Giovanni M. Pauletti

“…<b>Conclusions</b>: Experimental permeation data collected for selected APIs in FDA-approved oral cavity products will serve as a training set to aid the development of predictive computational models for improving algorithms that describe drug absorption from the oral cavity. …”
Get full text

Research Status and Development Trends of Deep Reinforcement Learning in the Intelligent Transformation of Agricultural Machinery by Jiamuyang Zhao, Shuxiang Fan, Baohua Zhang, Aichen Wang, Liyuan Zhang, Qingzhen Zhu

“…Looking forward, the DRL-driven smart transformation of agricultural machinery will focus on three key aspects: (1) The first aspect is developing a hybrid decision-making architecture based on model predictive control (MPC). This aims to enhance the strategic stability and decision-making interpretability of agricultural machinery (like unmanned tractors, harvesters, and drones) in complex and dynamic field environments. …”
Get full text

Aneuploidy screening in women of advanced age in the public healthcare setting of a low- to middle- income country – an observational cohort study by L Geerts, N Du Toit, M Schoeman

“…In the SA public sector, DS screening and confirmatory genetic testing are fully state subsidised for women of advanced maternal age (AMA) but, owing to the low positive predictive value of AMA-based screening, ultrasound-based screening is also offered. …”
Get full text