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Paul Ramia

A Scalable Radiomics- and Natural Language Processing–Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study
Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest
A simulation CT based radiomics model for detecting metastatic spinal bone lesions
Development of a generalizable natural language processing pipeline to extract physician-reported pain from clinical reports - Generated using publicly-available datasets and tested on institutional clinical reports for cancer patients with bone metastases
Development of a generalizable natural language processing pipeline to extract physician-reported pain scores from clinical reports in radiation oncology

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