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Development and validation of a predictive model for choledocholithiasis.

Raúl Huerta-ReynaLorenzo Guevara-TorresMario Aurelio Martínez-JiménezFrancisco Armas-ZarateJorge Aguilar-GarcíaLuis Ivan Waldo-HernándezMarco Ulises Martínez-Martínez
Published in: World journal of surgery (2024)
The developed algorithm accurately predicts choledocholithiasis non-invasively in patients with symptomatic gallstones. This tool has the potential to reduce reliance on costly or invasive procedures like magnetic resonance cholangiopancreatography and ERCP, offering a more efficient and cost-effective approach to patient management. The user-friendly calculator developed in this study could streamline diagnostic procedures, particularly in resource-limited healthcare settings, ultimately improving patient care.
Keyphrases
  • magnetic resonance
  • healthcare
  • machine learning
  • case report
  • deep learning
  • human health
  • risk assessment
  • climate change