Sensitivity and specificity of machine learning and deep learning algorithms in the diagnosis of thoracolumbar injuries resulting in vertebral fractures: A systematic review and meta-analysis

Sensitivity and specificity of machine learning and deep learning algorithms in the diagnosis of thoracolumbar injuries resulting in vertebral fractures: A systematic review and meta-analysis

Introduction: Clinicians encounter challenges in promptly diagnosing thoracolumbar injuries (TLIs) and fractures (VFs), motivating the exploration of Artificial Intelligence (AI) and Machine Learning (ML) and Deep Learning (DL) technologies to enhance diagnostic capabilities. Despite varying evidenc...

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Bibliographic Details
Main Authors: Hakija Bečulić, Emir Begagić, Amina Džidić-Krivić, Ragib Pugonja, Namira Softić, Binasa Bašić, Simon Balogun, Adem Nuhović, Emir Softić, Adnana Ljevaković, Haso Sefo, Sabina Šegalo, Rasim Skomorac, Mirza Pojskić
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Brain and Spine
Subjects:
Thoracolumbar injuries
Vertebral fractures
Machine learning
Deep learning
Artificial intelligence
Online Access:http://www.sciencedirect.com/science/article/pii/S2772529424000651

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