Pioneering Prostate Cancer Diagnosis: Evaluating AI Against Traditional Methods - A Systematic Literature Review

Zaki Farhan Virawan, Achmad Naufal

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ABSTRACT

 

Prostate cancer is one of the most common forms of men's cancer in the world and the understanding of its epidemiology is crucial to effective prevention, early detection and management strategies. This systematic review highlights the potential of artificial intelligence-based diagnostic methods to revolutionize the early diagnosis of prostate cancer. A comprehensive literature search was carried out using databases such as PubMed, Google Scholar and Scopus. After removing duplicates, titles and abstracts were examined in 279 studies and the following full texts were examined in 128 studies. We have ten studies to review in total. Therefore, we chose to review data for all 10 identified studies that applied AI techniques to detect ca prostate. The Paige Prostate Alpha AI system significantly enhances pathologists' diagnostic capabilities, leading to more accurate and effective prostate cancer detection. These limitations indicate that further research is required to address these issues and validate the results in a more diverse and controlled environment. AI-based diagnostic methods have shown significant promise in enhancing the early detection of prostate cancer. As technology continues to advance, integrating AI with traditional diagnostic approaches could lead to more effective, efficient, and accurate prostate cancer screening and diagnosis. Future studies should focus on large-scale clinical trials and real-world applications to validate these findings and facilitate the adoption of AI in clinical settings.

 

Keywords: Prostate Cancer, Artificial Intelligent, Deep Machine Learning, MRI


Kata Kunci


Kanker Prostat, Kecerdasan buatan, Pembelajaran mesin mendalam, MRI.

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Referensi


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https://doi.org/10.3389/fonc.2023.1170397.




DOI: https://doi.org/10.33024/mnj.v6i10.17042

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