A systematic review of artificial intelligence in prostate cancer

Derek J. Van Booven, Manish Kuchakulla, Raghav Pai, Fabio S. Frech, Reshna Ramasahayam, Pritika Reddy, Madhumita Parmar, Ranjith Ramasamy, Himanshu Arora

Research output: Contribution to journalReview articlepeer-review

12 Scopus citations


The diagnosis and management of prostate cancer involves the interpretation of data from multiple modalities to aid in decision making. Tools like PSA levels, MRI guided biopsies, genomic biomarkers, and Gleason grading are used to diagnose, risk stratify, and then monitor patients during respective follow-ups. Nevertheless, diagnosis tracking and subsequent risk stratification often lend itself to significant subjectivity. Artificial intelligence (AI) can allow clinicians to recognize difficult relationships and manage enormous data sets, which is a task that is both extraordinarily difficult and time consuming for humans. By using AI algorithms and reducing the level of subjectivity, it is possible to use fewer resources while improving the overall efficiency and accuracy in prostate cancer diagnosis and management. Thus, this systematic review focuses on analyzing advancements in AI-based artificial neural networks (ANN) and their current role in prostate cancer diagnosis and management.

Original languageEnglish (US)
Pages (from-to)31-39
Number of pages9
JournalResearch and Reports in Urology
StatePublished - 2021


  • Active surveillance
  • Artificial intelligence
  • Clinical trials
  • Prostate cancer

ASJC Scopus subject areas

  • Urology


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