Clinical Advances in Artificial Intelligence in Urology

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Nephrology & Urology".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 644

Special Issue Editor


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Guest Editor
Department of Urology, University General Hospital of Heraklion, University of Crete, Medical School, Heraklion, Greece
Interests: prostate biopsy; prostate cancer; endourology; prostate hyperplasia; urinary stone disease; laparoscopy; robotic surgery
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Special Issue Information

Dear Colleagues,

The science of artificial intelligence (AI) is advancing rapidly in various domains, including medicine. Similarly, AI has broadened its uses in the diagnostic and therapeutic domains of urology. Its application can significantly enhance the individualization of diagnosis and treatment and lower healthcare costs. However, its prospective uses and benefits are frequently overlooked or only partially understood. Additionally, to better comprehend this technology and safeguard patients and providers, potential ethical concerns, such as patient safety, cybersecurity, transparency, and data interpretability, need to be assessed before further use of AI is attempted. Numerous extremely complicated non-medical processes have already been investigated, and automated process optimization is possible thanks to recent developments in computer science. When used appropriately, creating AI models can result in more efficient patient-related data processing and analysis, improving urology patient diagnosis and treatment. Artificial intelligence (AI) using machine learning (ML) algorithms and artificial neural network (ANN) processes has been implemented to provide a precise and transversal perspective of a clinical scenario. We invite authors to submit papers for this Special Issue discussing the clinical application of AI in urology for both diagnosis and treatment.

Dr. Theodoros Tokas
Guest Editor

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Keywords

  • artificial intelligence
  • deep learning
  • artificial neural networks
  • computer
  • AI
  • machine learning

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Published Papers

This special issue is now open for submission.
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