A prospective study for the examination of peripheral blood smear samples in pediatric population using artificial intelligence.

Journal: Turkish journal of medical sciences
PMID: 40342329

Abstract

BACKGROUND/AIM: Peripheral blood smear (PBS) and bone marrow aspiration are gold standards of manual microscopy diagnostics for blood cell disorders. Nowadays, data-driven artificial intelligence (AI) techniques open new perspectives in digital hematology. This study proposes an AI learning technique for the classification of blood cells over PBS samples while increasing the sensitivity and specificity rates of the experts as a decision support system of a prediagnostic tool.

Authors

  • Elif Habibe Aktekin
    Department of Pediatrics Division of Pediatric Hematology-Oncology, Dr. Turgut Noyan Application and Research Center, Başkent University, Adana, Turkiye.
  • Mert Burkay Çöteli
    Mantiscope Medical Devices Ltd, Ankara, Turkiye.
  • Ayşe Erbay
    Department of Pediatrics Division of Pediatric Hematology-Oncology, Dr. Turgut Noyan Application and Research Center, Başkent University, Adana, Turkiye.
  • Nalan Yazici
    Department of Pediatrics Division of Pediatric Hematology-Oncology, Dr. Turgut Noyan Application and Research Center, Başkent University, Adana, Turkiye.

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