Evaluation of height prediction models: from traditional methods to artificial intelligence.

Journal: Pediatric research
PMID: 37735232

Abstract

BACKGROUND: Traditional methods for predicting adult height (AHP) rely on manual readings of bone age (BA). However, the incorporation of artificial intelligence has recently improved the accuracy of BA readings and their incorporation into AHP models.

Authors

  • Ana G Chávez-Vázquez
    Unit of Epidemiological Research in Endocrinology and Nutrition, Hospital Infantil de México Federico Gómez, Mexico City, Mexico.
  • Miguel Klünder-Klünder
    Research Subdirectorate, Hospital Infantil de México Federico Gómez, Mexico City, Mexico.
  • Nayely G Garibay-Nieto
    Pediatric Obesity Clinic and Wellness Unit, Hospital General de México "Dr. Eduardo Liceaga" and Hospital Ángeles del Pedregal, Mexico City, Mexico.
  • Desirée López-González
    Research Unit in Clinical Epidemiology, Hospital Infantil de México Federico Gómez, Mexico City, Mexico.
  • Mariana Sánchez-Curiel Loyo
    Radiology Department, Hospital Infantil de México Federico Gómez, Mexico City, Mexico.
  • América L Miranda-Lora
    Unit of Epidemiological Research in Endocrinology and Nutrition, Hospital Infantil de México Federico Gómez, Mexico City, Mexico. americaml@hotmail.com.

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