Authors
Matthew S Lee, Chloe T Shi, Tae-Hee Kim, Gianni A Morales Martinez, Ranveer Vasdev, Mark Waddle, Naoki Takahashi, Stephen A Boorjian, Abhinav Khanna
Published in
Clinical advances in hematology & oncology : H&O. Volume 24. Issue 5. Pages 292-300.
Abstract
Artificial intelligence (AI) is rapidly changing the field of medicine, and prostate cancer is no exception. The significant heterogeneity that characterizes the natural history of prostate cancer often leads to under- or overtreatment. Moreover, the already substantial burden of prostate cancer care on the health care system is predicted to rise significantly. By discerning patterns within immense, complex datasets, AI has the potential to augment the diagnosis, risk stratification, and treatment of prostate cancer beyond what is possible with existing clinical tools. In recent years, AI algorithms have achieved impressive diagnostic accuracy in the realms of imaging and histopathology interpretation, and AI-based biomarkers for risk stratification have been incorporated into major clinical guidelines. Early strides have also been made in radiation treatment planning, intraoperative surgical assistance and surgical education, and quality control. Moving forward, the prospective validation of novel AI algorithms across large, multi-institutional datasets is needed to minimize bias and ensure validity. Furthermore, it is the responsibility of providers across the continuum of prostate cancer care to ensure the safe and ethical integration of AI into clinical practice. This review summarizes the current state of AI applications in the diagnosis, risk stratification, and treatment of prostate cancer, highlighting recent advances and emerging opportunities in this ever-changing field.
PMID:
42550814
Bibliographic data and abstract were imported from PubMed on 05 Aug 2026.
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