CANCER GENOMICS AND AI: CREATING AI MODELS TO IDENTIFY GENOMIC ALTERATIONS IN CANCER, ENHANCING EARLY DETECTION AND PERSONALIZED TREATMENT STRATEGIES
DOI:
https://doi.org/10.69891/3060-4540.2025.56.98.001Keywords:
cancer genomics, artificial intelligence, early detection, personalized treatment, precision oncologyAbstract
The integration of artificial intelligence (AI) and cancer genomics has transformed precision oncology, enabling early detection and personalized treatment strategies. AI techniques, including machine learning and deep learning, analyze complex genomic data to uncover mutations and identify biomarkers. These approaches enhance early cancer detection through tools like liquid biopsies and optimize personalized treatments by predicting drug responses and refining immunotherapy. Despite significant advancements, challenges such as data privacy, model interpretability, and clinical integration remain. Future efforts focus on interdisciplinary collaboration, explainable AI, and federated learning to overcome these hurdles and further revolutionize cancer care
References
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.
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