Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait by Nicol Bernardinello, Federica Pezzuto, Lauren D’Sa, Luca Vedovelli, Chiara Giraudo, Anamaria Chelu, Anamaria Chelu, Cecilia de Chellis, Francesca Lunardi, Francesco Fortarezza, Francesca Boscaro, Elisabetta Cocconcelli, Paolo Spagnolo, Elisabetta Balestro, Fiorella Calabrese

“…Lung specimens revealed a significant overexpression of IL9 in the PPF compared to the nPPF group (p=0.049). Boruta algorithm analysis showed that lymphoid aggregates and traction bronchiectasis at diagnosis are the most important variables in determining the PPF status.ConclusionsThe present results increase the understanding of the pathological mechanisms of PPF, offering potential avenues for improved prognostication and therapeutic intervention.…”
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SiCRNN: A Siamese Approach for Sleep Apnea Identification via Tracheal Microphone Signals by Davide Lillini, Carlo Aironi, Lucia Migliorelli, Leonardo Gabrielli, Stefano Squartini

“…The final detection of <i>apnea</i> events is performed using an unsupervised clustering algorithm, specifically <i>k-means</i>. Multiple experimental runs were carried out to determine the optimal network configuration and the most suitable type and frequency range for the input data. …”
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The impact of Poyang Lake water level changes on the landscape pattern of wintering wading bird habitats by Feihong Yu, Jiancheng Zhai, Zhiqiang Huang, Jimei Chen, Fuqiang Han, Liaobo Wang

“…The cyclical rhythm of water level changes determines the dynamic variations in the wetland landscape pattern of Poyang Lake, directly impacting the habitat and survival of wintering migratory birds, particularly wading birds, which are most sensitive to these changes. This study employs an Artificial Neural Network (ANN) algorithm to interpret wetland landscapes using the Gao-Fen Satellite Images across 14 different water levels. …”
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Graph Based Cooperative Forwarding in Information Centric Vehicular Networks by Beri Surya Samantha, Nitul Dutta, Rajesh Mahadeva, Shashikant P. Patole, Gheorghita Ghinea

“…The prime objective of the algorithm is to reduce content retrieval time and optimize network overhead and throughput. …”
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Heterogeneous Graph Attention Networks for Scheduling in Cloud Manufacturing and Logistics by Dmitrii Fomin, Ilya Makarov, Mariia Voronina, Anna Strimovskaya, Vitaliy Pozdnyakov

“…Our model minimizes both manufacturing and logistics costs, achieving significant performance improvements over greedy algorithms and comparable results to strong genetic algorithms in large-scale scenarios with up to 20 locations. …”
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Development and Training of a Neural Network Filter for Satellite Images Processing by N. Andriyanov, A. Kim

“…As part of the study, the architecture of the autoencoder was developed, optimal hyperparameters were selected and the resulting neural network model was trained. …”
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What factors enhance students' achievement? A machine learning and interpretable methods approach. by Hui Mao, Ribesh Khanal, ChengZhang Qu, HuaFeng Kong, TingYao Jiang

“…This study addresses these limitations by employing an ensemble of five machine learning algorithms (SVM, DT, ANN, RF, and XGBoost) to model multivariate relationships between four behavioral and six instructional predictors, using final exam performance as our outcome variable. …”
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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“…The integration of such solutions can contribute to the development of decision support systems in psychiatry, optimizing therapeutic strategies, and improving the quality of care for patients with neuropsychological conditions. …”
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PERSONALIZED APPROACH TO THYROTOXICOSIS TREATMENT: THE HISTORY OF DOSIMETRIC CONCEPTS DEVELOPMENT by P. O. Rumyantsev, A. A. Trukhin, M. V. Degtyarev

“…Historically there were developed several methods for calculating effective therapeutic activity: prescription of standard activities (fixed activities) and personalized assessment of effective activity based on evaluation of individual radiobiokinetics, followed by the mathematical modeling. Accumulated variety of approaches to dosimetric planning of radionuclide therapy demonstrates that an optimal algorithm for calculation has not been developed so far. …”
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Research on image generation technology based on deep learning by Li Jinchen

“…Based on the above problems, this paper analyzes the methods of improving and optimizing the mainstream image generation algorithm from the perspectives of improving and optimizing the loss function, improving the space modeling, revising the structure of both the generator and discriminator, while speeding up the training process. …”
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Advancing Stability in Robot Manipulators: A Review of Recent Progress and Parameters by Shabnom Mustary, Mohammod Abul Kashem, Jannatul Mawya Sony, Nayem Hossain, Mohammad Asaduzzaman Chowdhury

“…Uses of Lyapunov and Passivity‐Based Control for key stability improvements incorporate robust solutions to nonlinear dynamics and uncertainties. …”
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Electrophysiological changes in the acute phase after deep brain stimulation surgery by Lucia K. Feldmann, Diogo Coutinho Soriano, Jeroen Habets, Valentina D'Onofrio, Jonathan Kaplan, Varvara Mathiopoulou, Katharina Faust, Gerd-Helge Schneider, Doreen Gruber, Georg Ebersbach, Hayriye Cagnan, Andrea A. Kühn

“…Background: With the introduction of sensing-enabled deep brain stimulation devices, characterization of long-term biomarker dynamics is of growing importance for treatment optimization. The microlesion effect is a well-known phenomenon of transient clinical improvement in the acute post-operative phase. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…A cost-effectiveness study estimated cost per point improvement in the Roland–Morris Disability Questionnaire. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…By integrating AI into Nigeria’s public health infrastructure, early detection and response can be improved, resource allocation optimized, and disease transmission minimized. …”
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Convolutional neural networks and vision transformers for Plankton Classification by Loris Nanni, Alessandra Lumini, Leonardo Barcellona, Stefano Ghidoni

“…The study considers the creation of ensembles combining different Convolutional Neural Network (CNN) models and transformer architectures to understand whether different optimization algorithms can result in more robust and efficient classification across various plankton datasets. …”
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Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. by Nicole A Doria-Rose, Han R Altae-Tran, Ryan S Roark, Stephen D Schmidt, Matthew S Sutton, Mark K Louder, Gwo-Yu Chuang, Robert T Bailer, Valerie Cortez, Rui Kong, Krisha McKee, Sijy O'Dell, Felicia Wang, Salim S Abdool Karim, James M Binley, Mark Connors, Barton F Haynes, Malcolm A Martin, David C Montefiori, Lynn Morris, Julie Overbaugh, Peter D Kwong, John R Mascola, Ivelin S Georgiev

“…Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. …”
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AI-Driven Robotics: Innovations in Design, Perception, and Decision-Making by Lei Li, Li Li, Mantian Li, Ke Liang

“…Artificial intelligence (AI), driven by large datasets and advanced algorithms, plays a pivotal role in addressing these challenges and advancing robotics. …”
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Integrating holographic counterparts for intelligent IoT consumer devices by M. Rajesh, M. Usha, Sathishkumar Veerappampalayam Easwaramoorthy

“…Advancements in quantum algorithms for predictive learning, self-optimization through more integrated machine learning models, and the development of standardised interoperability protocols to facilitate wider industrial usage are all areas that will be investigated in future research.…”
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Recent Advances in Multi-Agent Reinforcement Learning for Intelligent Automation and Control of Water Environment Systems by Lei Jia, Yan Pei

“…From the perspective of cooperative control, this paper investigates the modeling mechanisms and policy coordination strategies of MARL in key tasks such as water supply scheduling, hydro-energy co-regulation, and autonomous monitoring. …”
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AEM-D3QN: A Graph-Based Deep Reinforcement Learning Framework for Dynamic Earth Observation Satellite Mission Planning by Shuo Li, Gang Wang, Jinyong Chen

“…These features are then encoded into a reinforcement learning model that dynamically optimizes scheduling policies under multiple resource constraints. …”
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