[HTML][HTML] A narrative review of machine learning as promising revolution in clinical practice of scoliosis

K Chen, X Zhai, K Sun, H Wang, C Yang… - Annals of Translational …, 2021 - ncbi.nlm.nih.gov
Abstract Machine learning (ML), as an advanced domain of artificial intelligence (AI), is
progressively changing our view of the world. By implementing its algorithms, our ability to …

Artificial Intelligence in Scoliosis: Current Applications and Future Directions

H Zhang, C Huang, D Wang, K Li, X Han… - Journal of Clinical …, 2023 - mdpi.com
Scoliosis is a three-dimensional deformity of lateral bending and rotation of the spine.
Artificial intelligence (AI) is a set of theories and techniques for studying artificial intelligence …

Artificial intelligence clustering of adult spinal deformity sagittal plane morphology predicts surgical characteristics, alignment, and outcomes

WM Durand, R Lafage, DK Hamilton, PG Passias… - European Spine …, 2021 - Springer
Purpose AI algorithms have shown promise in medical image analysis. Previous studies of
ASD clusters have analyzed alignment metrics—this study sought to complement these …

Applications of artificial intelligence for adolescent idiopathic scoliosis: mapping the evidence

SN Goldman, AT Hui, S Choi, EK Mbamalu, P Tirabady… - Spine deformity, 2024 - Springer
Purpose Adolescent idiopathic scoliosis (AIS) is a common spinal deformity with varying
progression, complicating treatment decisions. Artificial intelligence (AI) and machine …

Classification of neurofibromatosis‐related dystrophic or nondystrophic scoliosis based on image features using bilateral cnn

Z He, Y Wang, X Qin, R Yin, Y Qiu, K He… - Medical Physics, 2021 - Wiley Online Library
Purpose We developed a system that can automatically classify cases of scoliosis
secondary to neurofibromatosis type 1 (NF1‐S) using deep learning algorithms (DLAs) and …

A data-driven approach to categorize patients with traumatic spinal cord injury: cluster analysis of a multicentre database

S Basiratzadeh, R Hakimjavadi, N Baddour… - Frontiers in …, 2023 - frontiersin.org
Background Conducting clinical trials for traumatic spinal cord injury (tSCI) presents
challenges due to patient heterogeneity. Identifying clinically similar subgroups using patient …

The state of machine learning in spine surgery: a systematic review

EM DelSole, WL Keck, AA Patel - Clinical Spine Surgery, 2022 - journals.lww.com
Study Design: This was a systematic review of existing literature. Objective: The objective of
this study was to evaluate the current state-of-the-art trends and utilization of machine …

Prediction of Fusion Rod Curvature Angles in Posterior Scoliosis Correction Using Artificial Intelligence

R Abedi, N Fatouraee, M Bostanshirin… - Archives of Bone …, 2024 - pmc.ncbi.nlm.nih.gov
Objectives: This study aimed to estimate post-operative rod angles in both concave and
convex sides of scoliosis curvature in patients who had undergone posterior surgery, using …

Artificial neural networks for the recognition of vertebral landmarks in the lumbar spine

F Galbusera, T Bassani, F Costa… - Computer Methods in …, 2018 - Taylor & Francis
The diagnosis and treatment of spinal disorders often requires the measurements of
anatomical parameters on radiographic projections, which is usually performed manually …

An automatic scoliosis diagnosis and measurement system based on deep learning

Z Tan, K Yang, Y Sun, B Wu, H Tao… - … on Robotics and …, 2018 - ieeexplore.ieee.org
Adolescent idiopathic scoliosis (AIS) is a three-dimensional structural deformity of the spine
which affects 1-4% of adolescents and causes not only deformed appearance but also …