Ricardo Correia

Text2FHIRwallet: Automated Generation of FHIR Patient Summaries from Unstructured Cardiology Reports Using Fine-Tuned Portuguese Language Models—Development and Evaluation of a Health Professional Wallet

Text2FHIRwallet demonstrates that domain-specific fine-tuning of a Portuguese-language pretrained language model achieves near-ceiling clinical NER accuracy, enabling scalable, interoperable, and privacy-compliant patient summary generation from unstructured cardiology text, offering an end-to-end pathway for integrating AI-driven NLP into clinical workflows and FHIR-based health information ecosystems.