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Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reports

Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reports

USCF Chen Scholar, Rima Arnout, MD, was part of a team whose research was recently published in the journal Nature focusing on recent innovations in cardiac ultrasound.

Big data can revolutionize research and quality improvement for cardiac ultrasound. Text reports are a critical part of such analyses. Cardiac ultrasound reports include structured and free text and vary across institutions, hampering attempts to mine text for useful insights. Natural language processing (NLP) can help and includes both statistical- and large language model-based techniques.

Read more in the journal Nature