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Диагностика злокачественных плевральных выпотов с помощью сверточных нейронных сетей путем морфометрического анализа изображений фаций плеврального экссудата
Хирургия. 2020. № 5. С. 42–48.
Objective. To estimate the possibility of diagnosis of malignant pleural effusion using convolutional neural networks of facies images of pleural exudates obtained by the method of wedge-shaped dehydration.
Material and methods. We studied 163 images of pleural fluid facies obtained by wedge-shaped dehydration in patients with various pleural effusions (10 nosological groups). Recognition and analysis were carried out using convolutional neural network. The images were divided into two groups — malignant effusion (n=65; 40%) and other diseases (n=98; 60%). Results. There were 131 photos selected for further investigation after pre-processing of images by eliminating defective ones, turning them into black and white format, cleaning of ‘noise’, cutting out the facies. Then the images were standardized. The method of rigid transformations with rotation for every 10 degrees was used. As a result, their number increased up to 4,585. Self-taught neural network analyzed the images of facies independently by separation of the fragments consisting of black and white dots and comparison of them with each other. Self-teaching and training of each neural network were ensured by random sampling of 80%
of images from the initial sample. Then the remaining 20% of the images were used as a control sample to assess the possibilities of recognition pleural effusion cause. Four options of convolutional neural networks were used. An accuracy of cancer detection ranged from 82% to 95.6%, benign diseases — from 84% to 94.7%. The neural network with the highest sensitivity was chosen.Conclusion. Automated image analysis system of pleural effusion facies using convolutional neural network ensured an accuracy of diagnosis of malignant pleural effusion in 95,6% of cases and other diseases in 90% of cases. The method is simple, efficient, cheap and reagentless.
Inês G., Скороход С. Н., Matteo d. V. et al., Communications in Nonlinear Science and Numerical Simulation 2027 Vol. 164 P. 1–13
The collective dynamics of spiking networks of neurons has been of central interest to both computational
neuroscience and network science. Over the past years, a new generation of neural
population models based on exact reductions (ER) of spiking networks have been developed.
However, most of these efforts have been limited to networks of neurons with simple dynamics
(e.g. the ...
Added: October 29, 2026
Чернявский А. А., Психиатрия 2026 Т. 24 № 2 С. 131–151
Background: existing tools for assessing depression do not take into account its contextualized nature. One of the prevailing spheres of human activity is labor activity, which may cause the occurrence of depression associated with professional activity. Occupational depression is a depressive state associated with chronic work stress. Because occupational activity may be a significant factor ...
Added: October 28, 2026
Association for Computational Linguistics, 2026.
While Large Language Models (LLMs) have revolutionized NLP, they remain prone to hallucinations, reasoning “mode-collapse” in open-ended generation, and a lack of factual provenance. The Automated Knowledge Base Construction (AKBC) workshop addresses a key missing piece of the generative era: structured knowledge. Knowledge Bases (KBs) serve as ground truth for fact verification, the semantic backbone ...
Added: October 28, 2026
Шахнович Е. Б., Кербиков О. Б., Kulaga E., Современная онкология 2015 Т. 17 № 1 С. 50–54
Гепатоцеллюлярный рак (гЦр) является одним из наиболее распространенных онкологических заболеваний в мире. Успех терапии гЦр напрямую зависит от диагностики заболевания на ранней стадии и своевременного назначения правильного лечения пациентам. согласно современным рекомендациям системная стандартная лекарственная химиотерапия не является оптимальным вариантом лечения пациентов с распространенным гЦр. в настоящее время единственным одобренным таргетным препаратом для лечения гЦр ...
Added: October 28, 2026
Nikitiuk B., Lenev D., Pisarev V. et al., Journal of Colloid and Interface Science 2026 Vol. 718 Article 140444
Hypothesis:Accurate determination of interfacial tension values is crucial for many modeling applications in the oil and gas industry. However, many of the presently used empirical and theoretical models show poor prediction accuracy and do not allow for direct consideration of the concentrations of gases and salts dissolved in the system as well as the specific ...
Added: October 28, 2026
Deshchenya V., Nikolay D. Kondratyuk, Sivakova A. et al., Chemical Engineering Sciences 2027 Vol. 337 Article 124616
Accurate prediction of complex formulation viscosity is crucial for the lubricant industry and engineering processes. However, developing generalizable models remains challenging due to the complexity of industrial mixtures and the scarcity of public experimental data, often resulting from corporate proprietary restrictions. This study presents a machine-learning workflow for viscosity estimation from a proprietary pseudonymized dataset, ...
Added: October 28, 2026
Zubov A., Zubov A., Малявко, Я. et al., Computer Physics Communications 2025 Vol. 317 Article 109860
The concept of representative volume (REV, or RVE in material sciences) is the cornerstone of continuum scale models – one needs to get the volume big enough so that it could be represented with an averaged value (scalar, vector or tensorial, etc.). While REV should be established in all larger scale simulations, this is rarely ...
Added: October 28, 2026
Roman Prosvirnin, Suslov A., Aleksei Soldatov et al., Computation 2026 Vol. 14 No. 10 Article 261
Abstract
Safety-aligned language models often encode that a request is harmful yet still comply with it. We turn this gap between internal recognition and observable behavior into an inference-time defense. The proposed activation-steering method uses a multiplicative operator that amplifies the residual-stream component along a harm-recognition direction. Intervention strength scales with the model’s own assessment of ...
Added: October 27, 2026
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Big Data and Cognitive Computing 2026 Vol. 10 No. 11 P. 1–52
Camera traps are a key tool for non-invasive wildlife monitoring, yet models trained on existing benchmarks often generalize poorly to new regions due to domain shift, class imbalance, and natural variability in illumination, season, and background. We introduce PACTraD, a benchmark of 116,973 annotated camera trap images collected in a protected area of the Baikal ...
Added: October 27, 2026
IEEE, 2026.
Proceedings of the X Scientific School "Dynamics of Complex Networks and their Applications"
(DCNA'2026) contain papers of reports of scientists and specialists in the field of intelligent technologies,
engineering education, research and design of complex networks.
DCNA'2026 was held from 10 to 12 September 2026 in Moscow, Russia, as a part of the International
Forum on Artificial Intelligence and ...
Added: October 26, 2026
Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Scientific data 2026 P. 1–20
We addressed the task of chemical characterization of the aerosol emitted by heated tobacco products (HTPs) and of the smoke emitted by conventional/commercial cigarettes, usually adopted as a reference. Emphasis was placed on quantifying constituents for enabling the identification of novel compounds through targeted and untargeted analyses, and the evaluation of reductions in toxicant exposure under ...
Added: October 26, 2026
Obsie E. Y., Zhan Y., Liu Y., Engineering Research Express 2026 Article 7
Maintaining plant health is crucial for crop quality, food security, and agricultural productivity. Although deep learning methods have shown strong potential for species, disease, and severity classification, most existing approaches tackle these tasks separately, failing to exploit shared representations and interdependencies among them. Furthermore, the variability of disease symptoms, such as subtle differences in size, ...
Added: October 22, 2026
Lev Pyatko, Sergey Aksenov, Regular and Chaotic Dynamics 2026 Vol. 31 No. 5 P. 794–813
In the circular restricted three-body problem, families of periodic and quasi-periodic orbits exist in the vicinity of the libration points and are of significant interest for practical applications. This work presents a neural network-based algorithm for orbit construction and station-keeping, applicable to both periodic and quasi-periodic orbits near collinear libration points. The method employs a ...
Added: October 19, 2026
Vorontsova T., М.: Академия, 2025.
The textbook has been prepared in accordance with the requirements of the federal state educational standards for secondary vocational education and is intended for studying the professional modules “Information Security in Information and Telecommunication Systems and Networks Using Software and Hardware‑Software Tools, Including Cryptographic Protection Tools” and “Information Security in Automated Systems Using Software and ...
Added: October 19, 2026
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 10 Article 330
Automated microscopic image analysis is essential for quantitative microbiology, yet manual acquisition and generic recognition models struggle with morphological variability and scene artifacts. We address both ends of this pipeline. First, we present a low-cost, open-source acquisition system, based on an Arduino UNO R3 microcontroller and NEMA 17 stepper motors, that automates focusing, magnification, and ...
Added: October 14, 2026
Springer, 2026.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XIV International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2025). The carefully selected papers cover ...
Added: October 13, 2026
Springer, 2026.
This book offers a comprehensive overview of the latest research, innovations, and practical applications in the field of sustainability, with a focus on construction materials and their use in building and civil engineering structures. As an outcome of the 3rd International Conference on Sustainability: Developments and Innovations (ICSDI 2026), this book presents a selection of ...
Added: October 13, 2026
Dmitriev A., Kornilov V., Batienkov R., Lecture Notes in Civil Engineering 2026 Vol. 886 P. 249–255
Numerous studies have provided compelling evidence that the probability distribution of avalanche sizes follows a power law, and that 1/f noise is present in the stochastic dynamics of landslides. We present a theoretical explanation of these phenomena within the framework of self-organized criticality theory, proposing a discrete-time model in the form of a sandpile cellular ...
Added: October 13, 2026
Dmitriev A., Shulman I., Lebedev A., Studies in Computational Intelligence 2026 Vol. 1265 P. 266–273
A discrete-time model is presented for the self-organization of the X/Twitter social network to the edge of a phase transition, characterized by avalanche-like propagation of information in the network. The model is based on the analogy between the critical dynamics of the X social network and sandpile cellular automata with Manna rule on the Chung-Lu ...
Added: October 13, 2026
Makarov D. M., Kalikin N., Fashchevsky K. A. et al., Electrochimica Acta 2026 Vol. 579 Article 150159
Machine learning (ML) has become a powerful tool for accelerating the development of carbon-based supercapacitors;
however, most published models assume that a single predictive framework can describe both conventional
porous carbons and hybrid carbon electrodes. Here, we test this assumption using a comprehensive
benchmark dataset and an extended literature-curated dataset enriched with synthesis- and electrolyte-related
descriptors. Three ML algorithms ...
Added: October 13, 2026
Marinin N., Getman A., Труды Института системного программирования РАН 2026 Т. 38 № 4 С. 123–142
This paper investigates a method for detecting DNS tunnels in network traffic using a neural network.
To achieve this, an analysis of current detection approaches was conducted, and a dataset for neural network
training was prepared. The proposed model takes as input a sequence of characters extracted from DNS
responses. The trained model demonstrated an F1-score close to ...
Added: September 11, 2026
Ребрейкина А. Б., Liaukovich K., Современная зарубежная психология 2024 Т. 13 № 2 С. 33–43
Создание методик диагностики на основе анализа движений глаз является особенно актуальным для оценки когнитивных функций у детей, которые не могут дать речевой или моторный ответ в силу своего возраста или из-за нарушений развития. Для таких детей использование объективных методов оценки когнитивных функций на основе айтрекинга может стать полезным диагностическим инструментом, дополняющим традиционные поведенческие опросники и ...
Added: September 8, 2026
Rakhlin N., Li N., Momotenko D. et al., American Journal of Speech-Language Pathology 2026 Vol. 35 No. 5 P. 1998–2015
Purpose:
We (a) investigated whether children of lower socioeconomic status (SES) are at a greater risk of developmental language disorder (DLD) than children of higher SES, based on standardized assessment; (b) identified the language skills most strongly affected by SES; and (c) examined which standardized and naturalistic measures best differentiate DLD in children from lower SES ...
Added: August 10, 2026
Karacharovskiy V., Ларина У. С., Резмерица А. А., Социологические исследования 2026 № 7 С. 60–75
Based on the neural network approach, the decomposition of the index of social mood in Russia for the period 2004-2024 was carried out and their dynamics for this period was modeled. The following issues are discussed: (a) the nature of the social mood' shocks in Russia, based on their connection with the concepts of politics ...
Added: May 14, 2026