Artificial intelligence in diagnosing breast cancer imaging profile than other predicting markers. Current and best future emerging technology
DOI:
https://doi.org/10.17720/ymbrr916Keywords:
Breast cancer, Mammography, Artificial intelligence, Computer-aided technique, Deep learningAbstract
Purpose: This research aims to underscore the significance of artificial intelligence in diagnosing breast cancer, contributing to precision medicine, and delves into current advancements and future requirements. Procedure: The data was collected from already published work on breast cancer imaging profile. Different websites including Google scholar etc were employed to fetch the relevant data for the current study. Results: The study reveals that diverse tools have been employed for precise image interpretation, assisting clinicians in prescribing accurate medications for more effective treatments. Artificial intelligence helps in medical science, such as computer-aided exposure and disease analysis, case-dependent reasoning, reasonable artificial intelligence, osteodetect method, and rainbow boxes, have demonstrated efficacy in diagnosing breast cancer. Different tools including Support vector machine, Cascade forward back-propagation network, Feed forward back-propagation network , k-nearest neighbor, Genetic algorithm as optimizer, Naive Bayes classifier, Deep learning technology show best performance for image processing and helpful in better medication prescriptions. Conclusion: In conclusion, it is crucial to recognize that the importance of artificial intelligence in interpreting breast imaging is evolving, not as a replacement for radiologists, but as a valuable aid, introducing new, effective, and efficient AI methodologies. Ongoing efforts are essential to further enhance artificial intelligence applications for more impactful outcomes in near future.
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