The use and applicability of machine learning algorithms in predicting the surgical outcome for patients with benign prostatic enlargement. Which model to use?

Journal: Archivio italiano di urologia, andrologia : organo ufficiale [di] Societa italiana di ecografia urologica e nefrologica
PMID: 34933537

Abstract

OBJECTIVES: Artificial intelligence (AI) is increasingly used in medicine, but data on benign prostatic enlargement (BPE) management are lacking. This study aims to test the performance of several machine learning algorithms, in predicting clinical outcomes during BPE surgical management.

Authors

  • Panagiotis Mourmouris
    2nd Department of Urology, Sismanogleio General Hospital, Athens Medical School, National and Kapodistrian University of Athens, Athens, Greece.
  • Lazaros Tzelves
    2nd Department of Urology, Sismanoglio Hospital, National and Kapodistrian University of Athens, Athens, Greece.
  • Georgios Feretzakis
    School of Science and Technology, Hellenic Open University, Patras, Greece.
  • Dimitris Kalles
    School of Science and Technology, Hellenic Open University, Patras, Greece.
  • Ioannis Manolitsis
    2nd Department of Urology, National and Kapodistrian University of Athens, Sismanogleio General Hospital, Athens. giannismanolit@gmail.com.
  • Marinos Berdempes
    2nd Department of Urology, National and Kapodistrian University of Athens, Sismanogleio General Hospital, Athens. marinosberdebes@hotmail.com.
  • Ioannis Varkarakis
    2nd Department of Urology, National and Kapodistrian University of Athens, Sismanogleio General Hospital, Athens. medvark3@yahoo.com.
  • Andreas Skolarikos
    2nd Department of Urology, National and Kapodistrian University of Athens, Sismanogleio Hospital, Athens, Greece. Electronic address: andskol@yahoo.com.

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