A Systematic Review of Artificial Intelligence in Prostate Cancer

Abstract

Derek J Van Booven,1 Manish Kuchakulla,2 Raghav Pai,2 Fabio S Frech,2 Reshna Ramasahayam,2 Pritika Reddy,2 Madhumita Parmar,2 Ranjith Ramasamy,2,3 Himanshu Arora1– 3 1John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; 2Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA; 3The Interdisciplinary Stem Cell Institute, Miller School of Medicine, University of Miami, Miami, FL, USACorrespondence: Himanshu Arora Email [email protected]: 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.Keywords: prostate cancer, active surveillance, clinical trials, artificial intelligence

Keywords

• prostate cancer
• active surveillance
• clinical trials
• artificial intelligence