ГЕНОМИКА РАКА И ИИ: СОЗДАНИЕ МОДЕЛЕЙ ИИ ДЛЯ ВЫЯВЛЕНИЯ ГЕНОМНЫХ ИЗМЕНЕНИЙ ПРИ РАКОВЫХ ЗАБОЛЕВАНИЯХ, УЛУЧШЕНИЕ РАННЕГО ВЫЯВЛЕНИЯ И ПЕРСОНАЛИЗИРОВАННЫХ СТРАТЕГИЙ ЛЕЧЕНИЯ

Авторы

  • Эминов Равшанджон Икромджон угли ассистент кафедры факультетской и госпитальной хирургии Ферганского медицинского института общественного здравоохранения, г. Фергана, https://orcid.org/0000-0002-4290-9840

DOI:

https://doi.org/10.69891/3060-4540.2025.56.98.001

Ключевые слова:

геномика рака, искусственный интеллект, раннее выявление, персонализированное лечение, точная онкология

Аннотация

Интеграция искусственного интеллекта (ИИ) и геномики рака преобразила точную онкологию, обеспечив раннее выявление и персонализированные стратегии лечения. Методы ИИ, включая машинное обучение и глубокое обучение, анализируют сложные геномные данные для обнаружения мутаций и идентификации биомаркеров. Эти подходы улучшают раннее выявление рака с помощью таких инструментов, как жидкая биопсия, и оптимизируют персонализированное лечение, прогнозируя реакцию на лекарства и совершенствуя иммунотерапию. Несмотря на значительные достижения, остаются такие проблемы, как конфиденциальность данных, интерпретируемость моделей и клиническая интеграция. Будущие усилия сосредоточены на междисциплинарном сотрудничестве, объяснимом ИИ и федеративном обучении для преодоления этих препятствий и дальнейшей революции в лечении рака

Библиографические ссылки

Perry Evans, Yong Kong, Michael Krauthammer Computational analysis in cancer exome sequencing. 2014.C. 219–227.

Alexis J. Clark, James W. Lillard A Comprehensive Review of Bioinformatics Tools for Genomic Biomarker Discovery Driving Precision Oncology // Genes. 2024.

Anwar Shams Leveraging State-of-the-Art AI Algorithms in Personalized Oncology: From Transcriptomics to Treatment // Diagnostics. 2024. № 19 (14). C. 2174–2174.

Anyou Wang [и др.]. Noncoding RNAs and deep learning neural network discriminate multi-cancer types. // arXiv: Molecular Networks. 2021.

Christopher J. Fong [и др.]. Abstract 1252: AI-derived predictions improve identification of real-world cancer driver mutations // Cancer Research. 2024.

Clare Fiala [и др.]. Can a Broad Molecular Screen Based on Circulating Tumor DNA Aid in Early Cancer Detection 2020. № 6 (5). C. 1372–1377.

Dr.Vinod Vegesna AI-Driven Personalized Medicine: A Frame Work for Tailored Cancer Treatment // International journal of innovative research in advanced engineering. 2024. № 06 (11). C. 747–752.

Ejike Innocent Nwankwo [и др.]. AI in personalized medicine: Enhancing drug efficacy and reducing adverse effects // International medical science research journal. 2024. № 8 (4). C. 806–833.

Eric R. Fearon Genetic and Epigenetic Alterations in Cancer 2020.C. 188–203.

Hakan Eraslan AI-Mediated Methods For Cancer Treatment 2024. № 1 (8). C. 25–25.

Hatijar Hatijar [и др.]. Application of Genomic Technology in Early Diagnosis and Personalized Treatment for Cancer Patients // Global international journal of innovative research. 2024. № 1 (2). C. 384–391.

Hongzhi Song [и др.]. Identification of Cancer Driver Genes by Integrating Multiomics Data with Graph Neural Networks // Metabolites. 2023. № 3 (13). C. 339–339.

Hui Chen [и др.]. Abstract 2315: AI-enabled precision oncology era: Advanced and interactive interpretation of next-gneneration sequencing (NGS) reports // Cancer Research. 2024.

Irene Dankwa-Mullan, Dilhan Weeraratne Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity // Cancer Discovery. 2022. (12). C. 1423–1427.

Jin Xu, Jianhui Yang, Xianjun Yu Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment // Journal of Hematology & Oncology. 2023. (16).

K. Aditya Shastry, H. A. Sanjay Cancer diagnosis using artificial intelligence: a review // Artificial Intelligence Review. 2021. C. 1–33.

Kungu Erisa The Significance of Artificial Intelligence and Machine Learning in the Identification of Immunotherapy Targets for Cancer: Advances, Challenges, and Future Directions 2024.

Lise Wei [и др.]. Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration. // British Journal of Radiology. 2023. C. 20230211–20230211.

Lorenzo Monserrat Genetic and Genomic Technologies: Next Generation Sequencing for Inherited Cardiovascular Conditions 2018.C. 97–117.

Manuel Schürch [и др.]. Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data // arXiv.org. 2024. (abs/2402.12190).

Md. Noumil Tousif [и др.]. Revolutionizing Cancer Therapy: The Role of Artificial Intelligence in Enhancing Treatment Efficacy 2023.C. 89–93.

Mehran Karimzadeh [и др.]. Deep generative AI models analyzing circulating orphan non-coding RNAs enable detection of early-stage lung cancer // Nature Communications. 2024. № 1 (15).

Michael J. Hall [и др.]. Incorporating genomic testing using next-generation sequencing (NGS) into clinical practice: Genetic counselors’ (GC) experience, knowledge, and perceived competence. // Journal of Clinical Oncology. 2014. (32).

Michael Vollenweider [и др.]. Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification // arXiv.org. 2024. (abs/2410.00509).

Murali Krishna Pasupuleti AI-Driven Mutation Detection: Transforming Genomic Data into Insights for Disease Prediction 2024. C. 1–28.

Nizamullah FNU [и др.]. AI in Healthcare: Breaking New Ground in the Management and Treatment of Cancer // Asian journal of engineering, social and health. 2024. № 10 (3). C. 2325–2343.

NULL AUTHOR_ID, Gaurav G Khandalkar, NULL AUTHOR_ID Artificial Intelligence Could be the Personalized Treatment Strategy for Cancer // International journal of pharmaceutical quality assurance. 2024. № 02 (15). C. 1017–1022.

Parikshit Bittla [и др.]. Exploring Circulating Tumor DNA (CtDNA) and Its Role in Early Detection of Cancer: A Systematic Review // Cureus. 2023. (15).

Mirakbarova, M., Xojamshukurov, N., Otajonov, A., Abdullayev, X., & Abdutolibov, M. (2024). TENEBRIO MOLITOR LICHINKASIDAN OLINGAN YOG’NING MIKROBIOLOGIK TAHLILI. Universal xalqaro ilmiy jurnal, 1(2), 60-66.

Pedro Henrique Zeraik Viduedo [и др.]. Harnessing the power of ai and machine learning for next-generation sequencing data analysis: a comprehensive review of applications, challenges, and future directions in precision oncology // Revista Ibero-Americana de Humanidades, Ciências e Educação. 2024. № 8 (10). C. 2898–2904.

Peter Hofland Early Detection of Ovarian Cancer May be Possible with Combination of Artificial Intelligence and Liquid Biopsies // Onco’zine. 2024.

Ryuji Hamamoto [и др.]. Current status and future direction of cancer research using artificial intelligence for clinical application // Cancer Science. 2024.

Sabira Arefin IDMap: Leveraging AI and Data Technologies for Early Cancer Detection // International Journal of scientific research and management. 2024.

Sarthak Bhatia [и др.]. Uncovering the Challenges From Algorithmic Bias Affecting the Marginalized Patient Groups in Healthcare // Social Science Research Network. 2024.

Serena Nik-Zainal Insights into cancer biology through next-generation sequencing. // Clinical Medicine. 2014. (14).

Shilian Dong [и др.]. Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning // eLight. 2023. (3).

Shriniket Dixit [и др.]. Personalized cancer vaccine design using AI-powered technologies // Frontiers in Immunology. 2024.

Siew-Kee Low, Hitoshi Zembutsu, Yusuke Nakamura Breast cancer: The translation of big genomic data to cancer precision medicine // Cancer Science. 2018. № 3 (109). C. 497–506.

Sohana Akter AI-Driven Precision Medicine: Transforming Personalized Cancer Treatment 2024. № 1 (2). C. 10–21.

Stefan Holdenrieder [и др.]. Pan-cancer screening by circulating tumor DNA (ctDNA) – recent breakthroughs and chronic pitfalls // Journal of laboratory medicine. 2022. № 4 (46). C. 247–253.

Tuğra Alp Terzi Using Artificial Intelligence for Personalized Cancer Treatment 2024. № 1 (8). C. 133–133.

William Huang, Chunli Zhao, Xiujun Fan Clinical Applications of Artificial Intelligence on Accuracy of Cancer Prediction, Detection, and Diagnosis 2020. № 10 (5). C. 470–478.

Yao Yao, Frank Chen, Qingpeng Zhang Optimized patient-specific immune checkpoint inhibitor therapies for cancer treatment based on tumor immune microenvironment modeling // Briefings in Bioinformatics. 2024. № 6 (25).

Yuanli Wang, Dawu Zheng The importance of precision medicine in modern molecular oncology. // Clinical Genetics. 2021. № 3 (100). C. 248–257.

Zodwa Dlamini The Application of AI in Precision Oncology: Tailoring Diagnosis, Treatment, and the Monitoring of Disease Progression to the Patient 2023.C. 1–25.

Emerging Non‐invasive Molecular Biomarkers for Early Cancer Detection 2022. C. 229–250.

Artificial Intelligence in Oncology: Current Capabilities, Future Opportunities, and Ethical Considerations // American Society of Clinical Oncology educational book. 2022. № 42. C. 842–851.

DrOGA: an artificial intelligence solution for driver-status prediction of genomics mutations in precision cancer medicine // IEEE Access. 2023. C. 1–1.

Effective Use of Computational Biology and Artificial Intelligence in the Domain of Medical Oncology 2024.C. 228–252.

Cancer classification using deep learning techniques and multi-omics data integration // International journal of research in advanced electronics engineering. 2024.

Опубликован

2025-01-24

Как цитировать

ГЕНОМИКА РАКА И ИИ: СОЗДАНИЕ МОДЕЛЕЙ ИИ ДЛЯ ВЫЯВЛЕНИЯ ГЕНОМНЫХ ИЗМЕНЕНИЙ ПРИ РАКОВЫХ ЗАБОЛЕВАНИЯХ, УЛУЧШЕНИЕ РАННЕГО ВЫЯВЛЕНИЯ И ПЕРСОНАЛИЗИРОВАННЫХ СТРАТЕГИЙ ЛЕЧЕНИЯ. (2025). Универсал международный научный журнал, 2(1), 114-124. https://doi.org/10.69891/3060-4540.2025.56.98.001