?
Assessment of Dendritic Cell Therapy Effectiveness Based on the Feature Extraction from Scientific Publications
P. 270–276.
Luparov A., Panov A. I., Suvorov R., Shvets A., Yarygin K., Volkova G.
Dendritic cells (DCs) vaccination is a promising way to contend cancer metastases especially in the case of immunogenic tumors. Unfortunately, it is only rarely possible to achieve a satisfactory clinical outcome in the majority of patients treated with a particular DC vaccine. Apparently, DC vaccination can be successful with certain combinations of features of the tumor and patients immune system that are not yet fully revealed. Difficulty in predicting the results of the therapy and high price of preparation of individual vaccines prevent wider use of DC vaccines in medical practice. Here we propose an approach aimed to uncover correlation between the effectiveness of specific DC vaccine types and personal characteristics of patients to increase efficiency of cancer treatment and reduce prices. To accomplish this, we suggest two-step analysis of published clinical trials results for DCs vaccines: first, the information extraction subsystem is trained, and, second, the extracted data is analyzed using JSM and AQ methodology.
In book
Vol. 2. , SciTePress, 2015.
Mungalov R. V., Vand N. S., Chudakov D. M. et al., Биоорганическая химия 2025 Т. 51 № 5 С. 1827–1837
The development of therapeutic antigen-specific T-cell receptors (TCRs) requires comprehensive preclinical validation of their functional activity. One of the approaches in the development of new drugs for cell therapy based on antigen-specific T lymphocytes is the modification of autologous T lymphocytes with endogenous T-cell receptors. The present work reviews modern laboratory platforms used to assess ...
Added: March 4, 2026
Biryukova K., Chelnokova D., Erkenova J. et al., Communications in Computer and Information Science 2024 Vol. 2364 CCIS P. 109 – 121
Added: February 25, 2026
Chepikov I., Karpov I., , in: 26th International Conference, AIED 2025, Palermo, Italy, July 22–26, 2025, Proceedings, Part I. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED.: Springer, 2025. P. 352 – 358.
Modern LLM models such as BERT, ChatGPT, DeepSeek have shown great potential in solving various tasks, including text classification, text generation, analysis and summary of documents. In this paper, we show that these models close to classical ML approaches based on decision trees not only in text processing, but also in processing classical tabular data ...
Added: September 4, 2025
I. V. Loginova, A. S. Piekalnits, E. A. Sabidaeva et al., Scientific and Technical Information Processing 2025 Vol. 52 No. 6 P. 738–751
The purpose of this paper is to advance and automate language models for extracting statements related to events and factors from text documents using the designed linguistic marker system. The paper presents the outcomes of text-mining models of events and factors extraction approbation on the example of analytical research in human potential, social sciences and ...
Added: July 18, 2025
Sohrabi M., Fathollahi-Fard A., Vasilii A. Gromov et al., Neural Computing and Applications 2025 Vol. 37 No. 18 P. 12253–12279
The generalized quadratic assignment problem (GQAP) poses a significant challenge in optimization, known for its NP-hard complexity and wide-ranging applications in supply chain and manufacturing contexts. While various metaheuristic algorithms have addressed the GQAP, this paper introduces a novel modification of the genetic algorithm (GA), namely the genetic engineering algorithm (GEA). A traditional GA initializes ...
Added: April 2, 2025
Morozov D., Garipov T., Lyashevskaya O. et al., Journal of Language and Education 2024 Vol. 10 No. 4 P. 71–84
Introduction: Numerous algorithms have been proposed for the task of automatic morpheme segmentation of Russian words. Due to the differences in task formulation and datasets utilized, comparing the quality of these algorithms is challenging. It is unclear whether the errors in the models are due to the ineffectiveness of algorithms themselves or to errors and inconsistencies ...
Added: January 7, 2025
Cham: Springer, 2024.
This multi-volume set, LNAI 14941 to LNAI 14950, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2024, held in Vilnius, Lithuania, in September 2024. ...
Added: November 22, 2024
Russo M., Pavone P., Meissner D. et al., Quality and Quantity 2025 Vol. 59 No. Suppl 1 P. S343–S367
In OECD countries, Science, Technology and Innovation (STI) policies were seen as key aspects of coping with the Covid-19 pandemic. Now that the pandemic is over, identifying which policy mix portfolios characterised countries in terms of their non-Covid-19 related and Covid-19 specific STI policies fills a knowledge gap on changes in STI policies induced by ...
Added: September 27, 2024
Parameter-Efficient Tuning of Transformer Models for Anglicism Detection and Substitution in Russian
Daniil Lukichev, Kryanina Darya, Anastasia Bystrova et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог». Вып. 22.Вып. 22.: [б.и.], 2023. P. 295–306.
Added: April 25, 2024
Shanghai: IEEE Computer Society, 2023.
The IEEE International Conference on Data Mining (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, ...
Added: March 20, 2024
D'yakonov A., Головина А. М., Прикладная математика и информатика 2023 Т. 61 № 74 С. 91–108
A methodology for finding patterns by solving machine learning problems with a teacher is described and applied to the analysis of national victimization survey data. Important features for machine learning models, interesting patterns and inconsistencies in the data are found. Experiments on estimating feature importance using different methods are described. ...
Added: March 18, 2024
Sergei O. Kuznetsov, Parakal E. G., Lecture Notes in Networks and Systems 2023 Vol. 776 P. 423–434
Inherently explainable Machine Learning (ML) models are able to provide explanations for their predictions by virtue of their construction. The explanations of a ML model are more comprehensible if they are expressed in terms of its input features. Our paper proposes an inherently explainable pipeline for document classification using pattern structures and Abstract Meaning Representation ...
Added: February 5, 2024
Switzerland: Springer, 2024.
This book constitutes revised papers from the International Workshops held at the 21st International Conference on Business Process Management, BPM 2023, in Utrecht, The Netherlands, during September 2023.
Papers from the following workshops are included:
• 7th International Workshop on Artificial Intelligence for Business Process Management (AI4BPM 2023)
• 7th International Workshop on Business Processes Meet Internet-of-Things (BP-Meet-IoT ...
Added: January 17, 2024
Северина Е. М., Ларионова М. Ч., Litera 2023 № 10 С. 211–222
The article considers a model of preparation of machine-readable (semantic) markup of texts for the Chekhov Digital project on the example of philological interpretation of individual significant elements of A. P. Chekhov's story "Death of an Official" and presentation of this information explicitly based on the standards of digital publication Text Encoding Initiative (TEI/XML). Based ...
Added: January 12, 2024
Кругликова В. Г., В кн.: Анализ речи: теоретические и прикладные аспекты: сборник научных статей.: [б.и.], 2023.
The article presents a comparative analysis of various language models used to generate texts and evaluates their effectiveness for the task of generating conversational speech. There are such models as GPT-3, BERT, LSTM involved in the comparative analysis. This study is part of a project of developing a system for generating dialogues in Russian. The ...
Added: December 10, 2023
Baklanova V., Kurkin A., Teplova T., China Finance Review International 2024 Vol. 14 No. 3 P. 522–548
Purpose – The primary objective of this research is to provide a precise interpretation of the constructed
machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype
index was constructed as well as several approaches of ...
Added: December 10, 2023
Kirina M., Человек: образ и сущность. Гуманитарные аспекты 2024 № 2(58) С. 176–204
The article focuses on the application of opinion mining techniques to evaluate user experience on the Hyperskill educational platform, using Python, Java, and Kotlin programming projects as the basis of analysis. The study utilizes sentiment analysis and keyword extraction methods to gauge users' attitudes towards the platform, learning process, and topics covered. To achieve this, ...
Added: December 9, 2023
Bolshakova E. I., Семак В. В., Интеллектуальные системы. Теория и приложения 2021 Т. 25 № 4 С. 239–242
An approach to automatic extraction of terms from an individual scientific text is reported, which combines known methods: linguistic patterns, statistical terminological measures, methods of graph ranking. The combined methods and stages for extracting, selection and ranking of terms are described, which are implemented for processing documents in Russian. The results of experiments on extracting ...
Added: November 23, 2023
Galitsky B., Ilvovsky D., Goncharova E., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог». Вып. 22.Вып. 22.: [б.и.], 2023.
We extend the concept of a discourse tree (DT) in the discourse representation of text towards data of various forms and natures. The communicative DT to include speech act theory, extended DT to ascend to the level of multiple documents, entity DT to track how discourse covers various entities were defined previously in computational linguistics, we now proceed ...
Added: November 10, 2023
Анташева М. С., Lobanova P., Isaeva J. K. et al., Социология: методология, методы, математическое моделирование 2023 № 57 С. 7–41
The information agenda broadcast by Chinese media resources is a source of up-to-date data on public opinion on key issues of social welfare. Due to the technical peculiarities of the organization of Chinese websites and the need to attract additional resources for automatic processing (parsing) of texts in Chinese, this topic is not widely represented in domestic and foreign studies. The ...
Added: November 9, 2023
I. K. Kusakin, Fedorets O. V., A. Y. Romanov, Scientific and Technical Information Processing 2023 Vol. 50 No. 3 P. 176–183
This paper discusses modern approaches to natural language processing and the application of machine learning models to the task of classifying short scientific texts in Russian. This study is devoted to the analysis of methods for vectorization of textual information, selection of a model for scientific paper clas- sification, and training of linguistic model BERT ...
Added: November 4, 2023