Augmented prediction of vertebral collapse after osteoporotic vertebral compression fractures through parameter-efficient fine-tuning of biomedical foundation models

Augmented prediction of vertebral collapse after osteoporotic vertebral compression fractures through parameter-efficient fine-tuning of biomedical foundation models

Abstract Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression aft...

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Bibliographic Details
Main Authors: Sibeen Kim, Inkyeong Kim, Woon Tak Yuh, Sangmin Han, Choonghyo Kim, Young San Ko, Wonwoo Cho, Sung Bae Park
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Subjects:
Compression fracture
Spine
Biomedical foundation model
Vision transformer
Parameter-efficient fine-tuning
Online Access:https://doi.org/10.1038/s41598-024-82902-w
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https://doi.org/10.1038/s41598-024-82902-w

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