Artificial Intelligence in Prostate Cancer Diagnosis

Year 2024, Volume: 19 Issue: 3, 151 - 156, 30.10.2024

Adem Alçın , Asıf Yıldırım

https://doi.org/10.33719/nju1557986

Abstract

Prostate cancer (PCa) is a cancer with a broad spectrum of biological behavior and a heterogeneous nature. To prevent overdiagnosis and overtreatment, and to detect clinically significant PCa, standardized scoring and grading systems are used in imaging and pathological examinations. However, reproducibility and agreement between readers in these diagnostic stages, which require experience, are low. Promising results have been achieved by integrating artificial intelligence (AI)-based applications into the diagnosis and management of PCa. In radiological and pathological imaging, computer-aided diagnostic tools have increased clinical efficiency and achieved diagnostic accuracy comparable to that of experienced healthcare professionals. This review provides an overview of AI applications used in radiological imaging, prostate biopsy, and histopathological examination in the diagnosis of PCa.

Keywords

Artificial intelligence, Prostate cancer, Machine learning, Deep learning, Radiomics

Prostat Kanseri Tanısında Yapay Zeka

Abstract

Prostat kanseri (PK), geniş bir biyolojik davranış spektrumuna ve heterojen bir yapıya sahip bir kanserdir. Aşırı tanı ve tedaviden kaçınmak ve klinik olarak anlamlı PK'ni tespit etmek amacıyla görüntüleme ve patolojik incelemelerde standardize edilmiş puanlama ve derecelendirme sistemleri kullanılmaktadır. Ancak, deneyim gerektiren bu tanısal aşamalarda okuyucular arasındaki tekrarlanabilirlik ve uyum düşüktür. Yapay zeka (YZ) tabanlı uygulamaların PK'nin tanı ve yönetimine entegre edilmesiyle umut verici sonuçlar elde edilmiştir. Radyolojik ve patolojik görüntülemede, bilgisayar destekli tanı araçları klinik verimliliği artırmış ve deneyimli sağlık profesyonellerine benzer tanısal doğruluk sağlamıştır. Bu inceleme, PK'nin tanısında kullanılan radyolojik görüntüleme, prostat biyopsisi ve histopatolojik incelemede YZ uygulamalarına genel bir bakış sunmaktadır.

Keywords

Yapay zeka, Prostat kanseri, Makine öğrenimi, Derin öğrenme, Radyomik

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