Combating Biomedical Misinformation through Multi-modal Claim Detection and Evidence-based Verification

• URL: http://arxiv.org/abs/2509.13888v1
• Date: Wed, 17 Sep 2025 10:31:09 GMT
• Title: Combating Biomedical Misinformation through Multi-modal Claim Detection and Evidence-based Verification
• Authors: Mariano Barone, Antonio Romano, Giuseppe Riccio, Marco Postiglione, Vincenzo Moscato,
• Abstract summary: CER (Combining Evidence and Reasoning) is a novel framework for biomedical fact-checking.<n>It integrates scientific evidence retrieval, reasoning via large language models, and supervised veracity prediction.<n>It effectively mitigates the risk of hallucinations, ensuring that generated outputs are grounded in verifiable, evidence-based sources.
• Score: 11.555285143713315
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Misinformation in healthcare, from vaccine hesitancy to unproven treatments, poses risks to public health and trust in medical systems. While machine learning and natural language processing have advanced automated fact-checking, validating biomedical claims remains uniquely challenging due to complex terminology, the need for domain expertise, and the critical importance of grounding in scientific evidence. We introduce CER (Combining Evidence and Reasoning), a novel framework for biomedical fact-checking that integrates scientific evidence retrieval, reasoning via large language models, and supervised veracity prediction. By integrating the text-generation capabilities of large language models with advanced retrieval techniques for high-quality biomedical scientific evidence, CER effectively mitigates the risk of hallucinations, ensuring that generated outputs are grounded in verifiable, evidence-based sources. Evaluations on expert-annotated datasets (HealthFC, BioASQ-7b, SciFact) demonstrate state-of-the-art performance and promising cross-dataset generalization. Code and data are released for transparency and reproducibility: https://github.com/PRAISELab-PicusLab/CER

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