Charos Khidirova

@tuit.uz

Computer Science, Computer Systems / Computer Engineering
Tashkent University of Information Technologies named after Muhammad al-Khwarizmi

Charos Khidirova


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https://researchid.co/hcharos

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Software, Computer Engineering
11

Scopus Publications

22

Scholar Citations

3

Scholar h-index

Scopus Publications

  • PatientEase—Domain-Aware RAG for Rehabilitation Instruction Simplification
    Rashid Nasimov, Akmalbek Abdusalomov, Charos Khidirova, Khosiyat Temirova, Alpamis Kutlimuratov, Shakhnoza Sadikova, Wonjun Jeong, Hyoungsun Choi, Taeg Keun Whangbo
    Bioengineering, 2025
    Background: Rehabilitation depends on using instructional materials, which many patients find difficult to understand; thus, their adherence to the safety and care may be affected. Text simplification systems used, in general, do not usually focus on procedure-oriented guidance or the degree of personalization required in rehabilitation settings. Methods: We present PatientEase, a domain-aware retrieval-augmented generation framework that changes rehabilitation instructions to simple words without changing the clinical meaning. PatientEase incorporates two complementary retrievers that is a corpus retriever that is tuned for rehabilitation and a user-aligned retriever that is conditioned on patient profiles, together with a role-structured, multi-agent rewriting pipeline; outputs can be further refined by using reinforcement learning from human feedback with a composite reward for readability, factuality, and clinician-preferred structure. Results: The latter was quite comprehensively compared in four benchmark tests against baselines, wherein SARI, FKGL, BERTScore, and MedEntail indices are employed, as well as clinician-patient assessments. PatientEase achieves 52.7 SARI and 92.1% factual entailment, and receives the highest fluency and simplicity ratings; ablations also underline each module’s role. Conclusions: PatientEase paves the road for safer, patient-centered communication in rehabilitation and lays the groundwork for trustworthy clinical dialogue systems.
  • Multi-Criteria Decision-Support System for Sustainable Management of the Aral Sea Basin Under Uncertainty
    Charos Khidirova, Yuanyao Lu, Alevtina Muradova, Komronbek Rakhimov
    Proceedings of 2025 International Conference on Sustainable Technology and Engineering I Coste 2025, 2025
  • Features of Intuitionistic Fuzzy Logic Application in Software Algorithms
    Charos Khidirova, Shakhnoza Sadikova, Nozima Jabborova, Feruza Sadikova
    Lecture Notes in Networks and Systems, 2024
  • Limited different schemes for mutual diffusion problems
    D. K. Muhamediyeva, S. Muminov, M. E. Shaazizova, Ch. Hidirova, Yu. Bahromova
    E3s Web of Conferences, 2023
    In the article, the problems of mutual diffusion, represented by a system of nonlinear differential equations of parabolic type, were modeled following numerical solving methods. The developed software was tested using various examples and obtained positive results. Mutual diffusion processes were visualized.
  • Intelligent System of Diagnosing and Predicting Cardiovascular Diseases
    Charos Khidirova, Ortik Ruzibaev, Sarvinoz Shoimova
    2022 International Conference on Information Science and Communications Technologies Icisct 2022, 2022
    The article discusses the development of an intelligent system used in the diagnosis and prognosis of cardiovascular diseases. The creation of neuro-expert systems designed to diagnose, predict and control the occurrence and development of cardiovascular diseases is proposed. human diseases. The possibilities of intelligent systems are demonstrated in specific examples of predicting and managing the health of patients by changing their lifestyles and taking certain medications. In computational experiments, the consequences of a manager’s impacts depend on the gender and age characteristics of patients and their current state of health.
  • Neuro-fuzzy algorithm for clustering multidimensional objects in conditions of incomplete data
    Ch M Khidirova, Sh Sh Sadikova, G M Nashvandova, S E Mirzaeva
    Journal of Physics Conference Series, 2021
    The paper is considered development of fuzzy expert system model for identifying faults in complex systems using data mining methods based on searching for hidden patterns in databases. The use of neural network technologies makes it possible to detect nonlinear dependencies of input and output data, improve the quality of an objective assessment of the state of complex technical objects, which ultimately will reduce the number of emergency situations during operation. A method is proposed for identifying the optimal number of fuzzy clusters in the space of training examples and determining, on their basis, the parameters of the membership functions for the input variables and inference results. Considered a neuro-fuzzy algorithm for clustering multidimensional objects in conditions of incompleteness and fuzzy initial information.
  • Machine learning methods as a tool for diagnostic and prognostic research in cardiovascular disease
    Charos Khidirova, Shakhnoza Sadikova, Shamil Mukhsinov, Gulrukhsor Nashvandova, Sarvinoz Mirzaeva
    International Conference on Information Science and Communications Technologies Applications Trends and Opportunities Icisct 2021, 2021
    Machine learning (ML) methods are the main tool of artificial intelligence, the use of which makes it possible to automate the processing and analysis of big data, to reveal hidden or non-obvious patterns on this basis, and to extract new knowledge. The review presents an analysis of scientific literature on the use of ML methods for diagnosing and predicting the clinical course of coronary heart disease. Provides information on reference databases, the use of which allows you to develop models and validate them (European ST-T Database, Cleveland Heart Disease database, Multi-Ethnic Study of Atherosclerosis, etc.). The advantages and disadvantages of individual ML methods (logistic regression, support vector machines, decision trees, naive Bayesian classifier, k-nearest neighbors) for the development of diagnostic and predictive algorithms are shown. The most promising ML methods include deep learning, which is implemented using multilayer artificial neural networks. It is assumed that the improvement of models based on ML methods and their introduction into clinical practice will help support medical decision-making, improve the effectiveness of treatment and optimize health care costs.
  • Comparative analysis of artificial neural network training Algorithms
    Charos Khidirova
    2020 International Conference on Information Science and Communications Technologies Icisct 2020, 2020
    This study compares training algorithms for artificial neural networks such as genetic, adaptive and hybrid. The “Fisher's Irises” were used as a data for the classification problem and KNIME Analytics Platform was chosen as the experimental environment. Given results comparison analysis of three methods training for neural networks and their parameters are presented. The choice of the optimal architecture was carried out on the basis of the classification algorithm, based on the graph of classification accuracy and error.
  • Methods and algorithms of determination of complexity of test questions for formation a database system of the adaptive test-control of knowledge
    Ch.M. Khidirova
    2017 International Conference on Information Science and Communications Technologies Icisct 2017, 2017
    In given paper offered methods and algorithms of determination of complexity of test questions for formation a database system of the adaptive test control for objective estimation of knowledge of students (pupils) in the course of training learning systems.
  • Elaboration of model and algorithms of the virtual control of knowledge in educational process
    Ch. M. Khidirova
    2011 5th International Conference on Application of Information and Communication Technologies Aict 2011, 2011
    In article is considered various algorithms and schemes of monitoring procedure of knowledge in virtual educational process of high schools and the set basic the characteristics, intended for system of the virtual control of knowledge is defined.
  • Implementation of virtual educational process at training of technical disciplines
    Ch. M. Khidirova
    4th International Conference on Application of Information and Communication Technologies Aict2010, 2010

RECENT SCHOLAR PUBLICATIONS

  • PatientEase—Domain-Aware RAG for Rehabilitation Instruction Simplification
    R Nasimov, A Abdusalomov, C Khidirova, K Temirova, A Kutlimuratov, ...
    Bioengineering 12 (11), 1204 , 2025
    2025
    Citations: 4
  • Использование технологий Интернет вещей в интеллектуальном кампусе
    ЧХ Алевтина Мурадова, Мубарак Абдужаппарова
    DigT Edu, 5 , 2025
    2025
  • Intuitionistic Fuzzy Rule-Based Decision-Making System
    K Ch.M.
    2025
  • INTUITIONISTIC FUZZY AGGREGATION OPERATORS IN MULTI-CRITERIA DECISION-MAKING
    FRM Khidirova Charos Murodilloevna
    Development of science 2, 150-157 , 2025
    2025
  • ANALYSIS OF TRADITIONAL METHODS FOR PREDICTING SOIL PRODUCTIVITY
    DZ Khidirova Charos
    American Journal of Technology and Applied Sciences 32, 15-20 , 2025
    2025
  • ANALYSIS OF THE OPERATION OF BIG DATA TECHNOLOGIES
    C Khidirova
    Indexing 1 (1) , 2024
    2024
  • АЛГОРИТМ РАЗДЕЛИТЕЛЬНОЙ ИЕРАРХИЧЕСКОЙ КЛАСТЕРИЗАЦИИ ДЛЯ ПРОГНОЗИРОВАНИЯ МУЛЬТИМОРБИДНЫХ ЗАБОЛЕВАНИЙ
    ЧМ Хидирова
    Science and innovation 3 (Special Issue 17), 217-223 , 2024
    2024
  • IMPORTANCE OF FUZZY LOGIC METHODS IN SOLVING PROBLEMS OF MEDICAL DIAGNOSIS AND PROGNOSIS
    KC Murodilloyevna, JNS Kizi
    Science and innovation 3 (Special Issue 17), 224-229 , 2024
    2024
  • YURAK-QON TOMIR KASALLIKLARINI BASHORAT QILISH VA TASHXIS QO ‘YISH INTELLEKTUAL TIZIMI
    C Xidirova, N Jabborova
    Raqamli Transformatsiya va Sun’iy Intellekt 1 (4), 92-100 , 2023
    2023
  • КЛАСТЕРЛАШ УСУЛИГА АСОСЛАНГАН МУЛЬТИМОРБИД БЕМОРЛАРНИНГ ҲОЛАТИНИ БАШОРАТ ҚИЛИШ АЛГОРИТМИ
    C Khidirova
    DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE 1 (4), 116-125 , 2023
    2023
  • «CVD RiskPrediction-2.0» –Yurak qon-tomir kasalliklari xavfini erta aniqlash va bashorat qilish intellektual tizimi
    C Khidirova
    2023
  • Применение искусственного интеллекта в клинических исследованиях сердечно-сосудистых заболеваний
    ЧМ Хидирова
    European Journal of «Interdisciplinary Research and Development», 325-331 , 2023
    2023
  • «Dasturiy ta’minot loyihalarini boshqarish» o‘quv qo‘llanma
    DMY Xidirova Ch.M.
    Toshkent, «Book Trade Ko» 2023. ISBN 978-9943-9242-2-2 , 2023
    2023
  • «Управление программными проектами» учебное пособие
    ДМЮ Хидирова Ч.М.
    Ташкент, «Book Trade Ko» 2023. -290 с. ISBN 978-9943-9242-1-5 , 2023
    2023
  • МЕТОДЫ ОПРЕДЕЛЕНИЯ СЛОЖНОСТИ ТЕСТОВЫХ ВОПРОСОВ В СИСТЕМЕ ВИРТУАЛЬНОГО ТЕСТ-КОНТРОЛЯ ЗНАНИЙ СТУДЕНТОВ
    БШ Раджабов, ЧМ Хидирова, М Миржамолова
    Academic research in educational sciences 4 (CSPU Conference 1), 199-203 , 2023
    2023
  • Limited different schemes for mutual diffusion problems
    DK Muhamediyeva, S Muminov, ME Shaazizova, C Hidirova, ...
    E3S Web of Conferences 401, 05057 , 2023
    2023
    Citations: 2
  • Features of Intuitionistic Fuzzy Logic Application in Software Algorithms
    C Khidirova, S Sadikova, N Jabborova, F Sadikova
    World Conference Intelligent System for Industrial Automation, 88-95 , 2022
    2022
    Citations: 1
  • Intelligent system of diagnosing and predicting cardiovascular diseases
    C Khidirova, O Ruzibaev, S Shoimova
    2022 International Conference on Information Science and Communications … , 2022
    2022
    Citations: 1
  • КОНЦЕПЦИЯ РЕШЕНИЯ ЗАДАЧИ ОПТИМИЗАЦИИ ТЕХНОЛОГИЧЕСКИХ РЕЖИМОВ ПРИ УПРАВЛЕНИИ ПЕРВИЧНОЙ ПЕРЕРАБОТКОЙ НЕФТИ
    Ш Гуломов, Ч Хидирова, М Дощанова
    ББК 34.4 П78, 157 , 2022
    2022
  • Machine learning methods as a tool for diagnostic and prognostic research in cardiovascular disease
    C Khidirova, S Sadikova, S Mukhsinov, G Nashvandova, S Mirzaeva
    2021 International Conference on Information Science and Communications … , 2021
    2021
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • Neuro-fuzzy algorithm for clustering multidimensional objects in conditions of incomplete data
    CM Khidirova, SS Sadikova, GM Nashvandova, SE Mirzaeva
    Journal of Physics: Conference Series 1901 (1), 012036 , 2021
    2021
    Citations: 5
  • PatientEase—Domain-Aware RAG for Rehabilitation Instruction Simplification
    R Nasimov, A Abdusalomov, C Khidirova, K Temirova, A Kutlimuratov, ...
    Bioengineering 12 (11), 1204 , 2025
    2025
    Citations: 4
  • Machine learning methods as a tool for diagnostic and prognostic research in cardiovascular disease
    C Khidirova, S Sadikova, S Mukhsinov, G Nashvandova, S Mirzaeva
    2021 International Conference on Information Science and Communications … , 2021
    2021
    Citations: 3
  • Comparative Analysis of Artificial Neural Network Training Algorithms
    C Khidirova
    2020 International Conference on Information Science and Communications … , 2020
    2020
    Citations: 3
  • Limited different schemes for mutual diffusion problems
    DK Muhamediyeva, S Muminov, ME Shaazizova, C Hidirova, ...
    E3S Web of Conferences 401, 05057 , 2023
    2023
    Citations: 2
  • Methods and algorithms of determination of complexity of test questions for formation a database system of the adaptive test-control of knowledge
    CM Khidirova
    2017 International Conference on Information Science and Communications … , 2017
    2017
    Citations: 2
  • Features of Intuitionistic Fuzzy Logic Application in Software Algorithms
    C Khidirova, S Sadikova, N Jabborova, F Sadikova
    World Conference Intelligent System for Industrial Automation, 88-95 , 2022
    2022
    Citations: 1
  • Intelligent system of diagnosing and predicting cardiovascular diseases
    C Khidirova, O Ruzibaev, S Shoimova
    2022 International Conference on Information Science and Communications … , 2022
    2022
    Citations: 1
  • Building systems of quality analysis adaptive test control of knowledge
    ЧМ Хидирова
    Молодой ученый, 111-114 , 2016
    2016
    Citations: 1
  • Использование технологий Интернет вещей в интеллектуальном кампусе
    ЧХ Алевтина Мурадова, Мубарак Абдужаппарова
    DigT Edu, 5 , 2025
    2025
  • Intuitionistic Fuzzy Rule-Based Decision-Making System
    K Ch.M.
    2025
  • INTUITIONISTIC FUZZY AGGREGATION OPERATORS IN MULTI-CRITERIA DECISION-MAKING
    FRM Khidirova Charos Murodilloevna
    Development of science 2, 150-157 , 2025
    2025
  • ANALYSIS OF TRADITIONAL METHODS FOR PREDICTING SOIL PRODUCTIVITY
    DZ Khidirova Charos
    American Journal of Technology and Applied Sciences 32, 15-20 , 2025
    2025
  • ANALYSIS OF THE OPERATION OF BIG DATA TECHNOLOGIES
    C Khidirova
    Indexing 1 (1) , 2024
    2024
  • АЛГОРИТМ РАЗДЕЛИТЕЛЬНОЙ ИЕРАРХИЧЕСКОЙ КЛАСТЕРИЗАЦИИ ДЛЯ ПРОГНОЗИРОВАНИЯ МУЛЬТИМОРБИДНЫХ ЗАБОЛЕВАНИЙ
    ЧМ Хидирова
    Science and innovation 3 (Special Issue 17), 217-223 , 2024
    2024
  • IMPORTANCE OF FUZZY LOGIC METHODS IN SOLVING PROBLEMS OF MEDICAL DIAGNOSIS AND PROGNOSIS
    KC Murodilloyevna, JNS Kizi
    Science and innovation 3 (Special Issue 17), 224-229 , 2024
    2024
  • YURAK-QON TOMIR KASALLIKLARINI BASHORAT QILISH VA TASHXIS QO ‘YISH INTELLEKTUAL TIZIMI
    C Xidirova, N Jabborova
    Raqamli Transformatsiya va Sun’iy Intellekt 1 (4), 92-100 , 2023
    2023
  • КЛАСТЕРЛАШ УСУЛИГА АСОСЛАНГАН МУЛЬТИМОРБИД БЕМОРЛАРНИНГ ҲОЛАТИНИ БАШОРАТ ҚИЛИШ АЛГОРИТМИ
    C Khidirova
    DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE 1 (4), 116-125 , 2023
    2023
  • «CVD RiskPrediction-2.0» –Yurak qon-tomir kasalliklari xavfini erta aniqlash va bashorat qilish intellektual tizimi
    C Khidirova
    2023
  • Применение искусственного интеллекта в клинических исследованиях сердечно-сосудистых заболеваний
    ЧМ Хидирова
    European Journal of «Interdisciplinary Research and Development», 325-331 , 2023
    2023