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20242026
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cs.CL2026

Can "AI" Be a Doctor? A Study of Empathy, Readability, and Alignment in Clinical LLMs

Mariano Barone, Francesco Di Serio, Roberto Moio +4

Large Language Models (LLMs) are increasingly deployed in healthcare, yet their communicative alignment with clinical standards remains insufficiently quantified. We conduct a mult…

cs.CL20251 cited

SOLVE-Med: Specialized Orchestration for Leading Vertical Experts across Medical Specialties

Roberta Di Marino, Giovanni Dioguardi, Antonio Romano +5

Medical question answering systems face deployment challenges including hallucinations, bias, computational demands, privacy concerns, and the need for specialized expertise across…

cs.CL2025

DART: A Structured Dataset of Regulatory Drug Documents in Italian for Clinical NLP

Mariano Barone, Antonio Laudante, Giuseppe Riccio +3

The extraction of pharmacological knowledge from regulatory documents has become a key focus in biomedical natural language processing, with applications ranging from adverse event…

cs.CL2025

IMB: An Italian Medical Benchmark for Question Answering

Antonio Romano, Giuseppe Riccio, Mariano Barone +2

Online medical forums have long served as vital platforms where patients seek professional healthcare advice, generating vast amounts of valuable knowledge. However, the informal n…

cs.CL2025

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

Mariano Barone, Antonio Romano, Giuseppe Riccio +2

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…

cs.CL2025

Combining Evidence and Reasoning for Biomedical Fact-Checking

Mariano Barone, Antonio Romano, Giuseppe Riccio +2

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…