Volume 34, Issue 12 (March 2024)
Studies in Medical Sciences 2024, 34(12): 760-771 |
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Kabaranzadghadim S, Gholizadeh-Ghaleh Aziz S, Babaei G, Mehranfar S, Mahmodlou R. ARTIFICIAL INTELLIGENCE AND GENE THERAPY OF BREAST CANCER. Studies in Medical Sciences 2024; 34 (12) :760-771
URL: http://umj.umsu.ac.ir/article-1-6143-en.html
URL: http://umj.umsu.ac.ir/article-1-6143-en.html
Shabnam Kabaranzadghadim 
, Shiva Gholizadeh-Ghaleh Aziz * , Ghader Babaei , Sahar Mehranfar , Rahim Mahmodlou
, Shiva Gholizadeh-Ghaleh Aziz * , Ghader Babaei , Sahar Mehranfar , Rahim Mahmodlou
MD-Ph.D. in Molecular Medicine, Assistant Professor of Urmia University of Medical Sciences, Urmia, Iran (Corresponding Author) , gholizadeh.sh@umsu.ac.ir
Abstract: (2496 Views)
Background & Aims: Gene therapy is used in various diseases such as cancer. Breast cancer is the most common malignancy in women worldwide, which shows the necessity of using innovative approaches in treatment methods. The ability of artificial intelligence algorithms to process large data, complex patterns, and classify them can be used to improve the process of gene therapy in breast cancer. The aim of this article is to review the available information and emphasize the applications of artificial intelligence in targeted gene therapy for breast cancer.
Materials & Methods: To carry out this study we used the articles on PubMed databases by searching for related keywords to collect information.
Results: By designing artificial intelligence algorithms and analyzing very complex molecular pathways in the human body and sampling the experiences of scientists and doctors in clinical studies and simulating biological processes related to the regulation of gene expression in the human body, the effectiveness of gene carriers, control of gene delivery parameters/medicine and modeling of cells minimized the rate of medical errors and with early diagnosis of the disease and predicting the effectiveness of the medicine, it provided patient-centered treatments of the effectiveness of new treatments such as gene therapy with the least complications at the highest level.
Conclusion: In recent decade, many efforts have been made to use all types of gene therapy for breast cancer patients with the least complications and the most effectiveness. Therefore, artificial intelligence is a powerful tool for optimizing early diagnosis and treatment for breast cancer. It’s combination with interdisciplinary sciences in improving the health of the society is a very interesting topic for scientists, but due to the limitations that exist for its use, such as ethical cases and high costs, it should be done with high precision and sufficient studies.
Materials & Methods: To carry out this study we used the articles on PubMed databases by searching for related keywords to collect information.
Results: By designing artificial intelligence algorithms and analyzing very complex molecular pathways in the human body and sampling the experiences of scientists and doctors in clinical studies and simulating biological processes related to the regulation of gene expression in the human body, the effectiveness of gene carriers, control of gene delivery parameters/medicine and modeling of cells minimized the rate of medical errors and with early diagnosis of the disease and predicting the effectiveness of the medicine, it provided patient-centered treatments of the effectiveness of new treatments such as gene therapy with the least complications at the highest level.
Conclusion: In recent decade, many efforts have been made to use all types of gene therapy for breast cancer patients with the least complications and the most effectiveness. Therefore, artificial intelligence is a powerful tool for optimizing early diagnosis and treatment for breast cancer. It’s combination with interdisciplinary sciences in improving the health of the society is a very interesting topic for scientists, but due to the limitations that exist for its use, such as ethical cases and high costs, it should be done with high precision and sufficient studies.
Type of Study: Review article |
Subject:
Oncology
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