Real-time detection of acromegaly from facial images with artificial intelligence.

Journal: European journal of endocrinology
PMID: 36747333

Abstract

OBJECTIVE: Despite improvements in diagnostic methods, acromegaly is still a late-diagnosed disease. In this study, it was aimed to automatically recognize acromegaly disease from facial images by using deep learning methods and to facilitate the detection of the disease.

Authors

  • Muhammed Kizilgul
    1 Department of Endocrinology and Metabolism, Diskapi Teaching and Research Hospital, Ankara, Turkey.
  • Rukiye Karakis
    Sivas Cumhuriyet University, Faculty of Technology, Software Engineering Department, Sivas, Turkey.
  • Nurettin Dogan
    Selçuk University, Faculty of Technology, Computer Engineering Department, Konya, Turkey.
  • Hayri Bostan
    University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Department of Endocrinology, Ankara, Turkey.
  • Muhammed Mutlu Yapici
    Ankara University, Elmadağ Vocational School, Computer Technologies Department, Ankara, Turkey.
  • Umran Gul
    University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Department of Endocrinology, Ankara, Turkey.
  • Bekir Ucan
    1 Department of Endocrinology and Metabolism, Diskapi Teaching and Research Hospital, Ankara, Turkey.
  • Elvan Duman
    Burdur Mehmet Akif Ersoy University, Faculty of Technology, Software Engineering Department, Burdur, Turkey.
  • Hakan Duger
    University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Department of Endocrinology, Ankara, Turkey.
  • Erman Cakal
    1 Department of Endocrinology and Metabolism, Diskapi Teaching and Research Hospital, Ankara, Turkey.
  • Omer Akin
    TOBB ETU, Faculty of Science and Literature, Mathematics Department, Ankara, Turkey.

Keywords

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