A supervised machine learning approach for predicting the need for postsurgical intervention in acromegaly.

Journal: Neurosurgical focus
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: Patients with growth hormone (GH)-secreting pituitary adenomas (PAs) experience various symptoms and comorbidities, which can ultimately lead to increased mortality. This study aimed to develop and validate a machine learning (ML) model for predicting long-term outcomes in patients with GH-secreting PAs following endonasal transsphenoidal surgery (ETS).

Authors

  • Yuki Shinya
    1Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Abdul Karim Ghaith
    Mayo Clinic Neuro-Informatics Laboratory, Mayo Clinic, Rochester, Minnesota, USA; Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, USA.
  • Sukwoo Hong
    1Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Justine S Herndon
    3Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, Mayo Clinic, Rochester, Minnesota; and.
  • Sandhya R Palit
    1Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Dana Erickson
    Division of Endocrinology, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, USA.
  • Irina Bancos
    Division of Endocrinology, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, USA.
  • Miguel Sáez-Alegre
    Servicio De Neurocirugía, Hospital Universitario La Paz, Madrid, Spain. Electronic address: miksaezalegre@gmail.com.
  • Ramin A Morshed
    1Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Carlos Pinheiro Neto
    4Department of Otolaryngology-Head and Neck Surgery, Mayo Clinic, Rochester, Minnesota.
  • Fredric B Meyer
    1Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.
  • John L D Atkinson
    1Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Jamie J Van Gompel
    1Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.

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