چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده | نفر چندم مقاله |
|---|---|
| علیرضا لطفی | اول |
| فرشته امیدوار | دوم |
| هادی صالح پور | سوم |
| مرتضی قوجازاده | چهارم |
| عنوان | متن |
|---|---|
| خلاصه مقاله | Introduction: Breast cancer is a common cancer that starts in the breast cells and can spread to other parts of the body. Symptoms include lumps, skin changes, and nipple discharge. Early detection is crucial, and various treatments are available, such as surgery, radiation, and chemotherapy. With advances in detection and treatment, survival rates have improved. Breast cancer is the most common cancer in women worldwide. In 2020, around 2.3 million new cases of breast cancer were reported, and 685,000 people died from the disease. It's most prevalent in developed countries, but it's a growing problem in developing countries, where access to medical care is limited. Men can also develop the disease, but it's rare. Epigenetic modifications play a role in breast cancer development, including DNA methylation, histone modification, and non-coding RNA. Environmental factors, aging, genetics, and lifestyle also contribute to the disease. Identifying the interactions between these factors is a current field of research. Methods: A comprehensive systematic search using the terms such as 'Breast Cancer', 'Artificial Intelligence', 'machine learning', ' Epigenomics' as keywords, was conducted in three Major Online Databases; PubMed, Scopus and Web of Science up to March 2023. The database search also contained gray literature and manual search. Two Independent reviewers screened the retrieved publications. All studies that use Artificial Intelligence (AI) models or machine learning algorithms to analyze epigenomic data collected for breast cancer research were included. Then studies that met our inclusion criteria were critically appraised by two authors independently. Microsoft Office Excel 2021 software is used to extract data such as machine learning algorithms, most used genes and mutations. Additionally, for screening purposes, we utilized the 'Rayyan' online platform. Results: We retrieved 302 relevant studies from online databases. After a thorough examination of the titles and abstracts and the removal of duplicate publications(n=80), 235 studies were eliminated. In 23 cases of disagreement between two authors, the opinion of the third author was the determiner. The full texts of 67 papers were reviewed. Eventually 17 studies met our inclusion criteria and included in this study. Conclusion: In conclusion, the integration of Artificial Intelligence (AI) into epigenetic analysis presents a promising solution to enhancing our understanding of breast cancer development. AI models can make use of large datasets to identify patterns in DNA methylation or histone modification that are associated with breast cancer risk and treatment outcomes. With AI, we can even predict how environmental factors contribute to epigenetic changes that influence breast cancer development. The application of AI to epigenetic data analysis provides researchers with a powerful tool to further explore the underlining mechanisms of breast cancer and find new targets for diagnosis, treatment, and prevention. |
| کلمات کلیدی | AI, Breast Cancer, Epigenetics |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| 1 (1).docx | 1403/02/30 | 16099 | دانلود |
| 01.jpg | 1402/10/19 | 82539 | دانلود |
| 02.pdf | 1402/10/19 | 62480 | دانلود |
| abstract.pdf | 1402/10/19 | 813510 | دانلود |
| 28_750_AliReza Lotfi.jpg | 1402/10/19 | 278496 | دانلود |
