Diagnostic performance of artificial intelligence in detection of renal cell carcinoma: a systematic review and meta-analysis.

Journal: BMC cancer
PMID: 39871201

Abstract

OBJECTIVES: The detection of renal cell carcinoma (RCC) tumors in the earlier stages is of great importance for more effective treatment. Encouraged by the key role of imaging in the management of RCC, we conducted a systematic review and meta-analysis of the studies that made use of artificial intelligence (AI) for the detection of RCC to quantitatively determine the performance of AI for distinguishing related renal lesions.

Authors

  • Mahdi Gouravani
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: Mgouravani@yahoo.com.
  • Mohammad Shahrabi Farahani
    Medical Students Research Committee, Shahed University, Tehran, Iran. Electronic address: mfarahani55401@gmail.com.
  • Mohammad Amin Salehi
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: mohamsa@gmail.com.
  • Shayan Shojaei
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • Sina Mirakhori
    Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Hamid Harandi
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • Soheil Mohammadi
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: soheil.mhm@gmail.com.
  • Ramy R Saleh
    Department of Oncology, McGill University, Montreal, QC, H3A 0G4, Canada.

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