Fig. 1 | Scientific Reports

Fig. 1

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

Fig. 1

Workflow of VC prediction model development. MRI pre-processing includes N4 bias field correction, cropping to the region of interest, and intensity normalization. Image model design highlights the Vision Transformer (ViT) architecture with BiomedCLIP pre-trained weights and parameter-efficient fine-tuning using Low-Rank Adaptation (LoRA). Additional techniques explored to further enhance the model’s performance include augmented prediction with adjacent MRI frames and addition of clinical features via a multi-layer perceptron (MLP). Model training and evaluation involve hyperparameter tuning, internal validation using 10 random splits, and external validation.

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