Papers by Fatemeh Haghighi

1 papers
RadEval: A framework for radiology text evaluation (2025.emnlp-demos)

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Challenge: Evaluating automated radiology report generation systems remains a fundamental challenge in the development of safe, accurate, and clinically useful medical AI.
Approach: They propose a unified, open-source framework for evaluating radiology texts that consolidates a diverse range of metrics from classic ngram overlap (BLEU) and contextual measures (BERTScore) to clinical concept-based scores (GREEN).
Outcome: The framework consolidates a diverse range of metrics from ngram overlap (BLEU) and contextual measures (BERTScore) to clinical concept-based scores (F1CheXbert, F1RadGraph, RaTEScore, SRR-BERT, TemporalEntityF1) and advanced LLMbased evaluators (GREEN).

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