International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 6 Issue 6
November-December 2024
Indexing Partners
Applications of AI (Artificial Intelligence) In Diagnosis of Breast Cancer
Author(s) | Ruhika Paliwal |
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Country | United Arab Emirates |
Abstract | Breast cancer is a leading cause of cancer-related deaths worldwide. Early detection and accurate diagnosis are crucial for improving patient outcomes. Artificial intelligence (AI) has emerged as a promising tool in the fight against breast cancer. This research report explores the potential applications of AI in various stages of breast cancer management, including early detection, diagnosis, treatment planning, and prognosis prediction. AI algorithms can analyze mammograms and other imaging data to identify suspicious lesions with greater accuracy than traditional methods. Additionally, AI-powered tools can assist in the classification of breast tumors, helping to determine the most appropriate course of treatment. Furthermore, AI can be used to predict the likelihood of recurrence and metastasis, enabling personalized monitoring and follow-up care. This research report presents a comprehensive review of the current state of AI in breast cancer research and highlights the potential benefits and challenges associated with its implementation. By leveraging the power of AI, healthcare providers can improve breast cancer outcomes and enhance the quality of life for patients. |
Keywords | Breast Cancer, AI, Application Of AI |
Field | Computer > Artificial Intelligence / Simulation / Virtual Reality |
Published In | Volume 6, Issue 5, September-October 2024 |
Published On | 2024-10-03 |
Cite This | Applications of AI (Artificial Intelligence) In Diagnosis of Breast Cancer - Ruhika Paliwal - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.27787 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i05.27787 |
Short DOI | https://doi.org/g688v4 |
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