Artificial intelligence in stone disease

Vishnu Ganesan, Margaret S. Pearle

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations


Purpose of reviewArtificial intelligence (AI) is the ability of a machine, or computer, to simulate intelligent behavior. In medicine, the use of large datasets enables a computer to learn how to perform cognitive tasks, thereby facilitating medical decision-making. This review aims to describe advancements in AI in stone disease to improve diagnostic accuracy in determining stone composition, to predict outcomes of surgical procedures or watchful waiting and ultimately to optimize treatment choices for patientsRecent findingsAI algorithms show high accuracy in different realms including stone detection and in the prediction of surgical outcomes. There are machine learning algorithms for outcomes after percutaneous nephrolithotomy, extracorporeal shockwave lithotripsy, and for ureteral stone passage. Some of these algorithms show better predictive capabilities compared to existing scoring systems and nomograms.SummaryThe use of AI can facilitate the development of diagnostic and treatment algorithms in patients with stone disease. Although the generalizability and external validity of these algorithms remain uncertain, the development of highly accurate AI-based tools may enable the urologist to provide more customized patient care and superior outcomes.

Original languageEnglish (US)
Pages (from-to)391-396
Number of pages6
JournalCurrent opinion in urology
Issue number4
StatePublished - Jul 1 2021


  • artificial intelligence
  • endourology
  • machine learning
  • nephrolithiasis
  • urolithiasis

ASJC Scopus subject areas

  • Urology


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