Pediatric fracture overgrowth is an unpredictable complication of long bone fractures in children, leading to excessive growth of the injured limb and resulting in limb length discrepancies (LLDs) and angular deformities that impact mobility and quality of life. Traditional methods struggle to predict at-risk children, hindering early detection and management. Artificial intelligence (AI), including machine learning and deep learning, offers advanced data analysis capabilities to enhance predictive accuracy and personalize treatment strategies. This comprehensive review explores the current understanding of pediatric fracture overgrowth, examines AI applications in medicine and orthopedics, evaluates potential AI applications specific to fracture overgrowth, and discusses ethical considerations and patient-centric approaches. We highlight how AI can improve diagnostic precision, facilitate early intervention, and optimize clinical outcomes. Though direct studies on AI in fracture overgrowth are limited, evidence from related areas underscores its potential. Embracing AI could revolutionize pediatric fracture management, leading to earlier detection, targeted interventions, and better outcomes for affected children.

The Role of Artificial Intelligence in Predicting and Managing Pediatric Fracture Overgrowth: A Comprehensive Review

Marletta, Daniela Alessia;Nanni, Matteo;Giuca, Gabriele;Sanzarello, Ilaria;Zampogna, Biagio;Leonetti, Danilo
2024-01-01

Abstract

Pediatric fracture overgrowth is an unpredictable complication of long bone fractures in children, leading to excessive growth of the injured limb and resulting in limb length discrepancies (LLDs) and angular deformities that impact mobility and quality of life. Traditional methods struggle to predict at-risk children, hindering early detection and management. Artificial intelligence (AI), including machine learning and deep learning, offers advanced data analysis capabilities to enhance predictive accuracy and personalize treatment strategies. This comprehensive review explores the current understanding of pediatric fracture overgrowth, examines AI applications in medicine and orthopedics, evaluates potential AI applications specific to fracture overgrowth, and discusses ethical considerations and patient-centric approaches. We highlight how AI can improve diagnostic precision, facilitate early intervention, and optimize clinical outcomes. Though direct studies on AI in fracture overgrowth are limited, evidence from related areas underscores its potential. Embracing AI could revolutionize pediatric fracture management, leading to earlier detection, targeted interventions, and better outcomes for affected children.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3322129
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact